Overview

Brought to you by YData

Dataset statistics

Number of variables59
Number of observations584707
Missing cells12982987
Missing cells (%)37.6%
Total size in memory263.2 MiB
Average record size in memory472.0 B

Variable types

Text59

Dataset

DescriptionBirds NMNH Extant Specimen Records (USNM) 0002610-250325103851331
URLhttps://doi.org/10.15468/hnhrg3

Alerts

institutionID has constant value "urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "BIRDS" Constant
datasetName has constant value "NMNH Extant Biology" Constant
basisOfRecord has constant value "PreservedSpecimen" Constant
kingdom has constant value "Animalia" Constant
phylum has constant value "Chordata" Constant
class has constant value "Aves" Constant
taxonRank has constant value "subspecies" Constant
recordNumber has 584589 (> 99.9%) missing values Missing
recordedBy has 7169 (1.2%) missing values Missing
lifeStage has 459596 (78.6%) missing values Missing
associatedMedia has 26145 (4.5%) missing values Missing
associatedSequences has 580220 (99.2%) missing values Missing
occurrenceRemarks has 572381 (97.9%) missing values Missing
eventDate has 41219 (7.0%) missing values Missing
startDayOfYear has 55198 (9.4%) missing values Missing
endDayOfYear has 55020 (9.4%) missing values Missing
year has 41219 (7.0%) missing values Missing
month has 53375 (9.1%) missing values Missing
day has 74043 (12.7%) missing values Missing
verbatimEventDate has 235551 (40.3%) missing values Missing
habitat has 567499 (97.1%) missing values Missing
continent has 12722 (2.2%) missing values Missing
waterBody has 558621 (95.5%) missing values Missing
stateProvince has 93864 (16.1%) missing values Missing
county has 353976 (60.5%) missing values Missing
locality has 107553 (18.4%) missing values Missing
minimumElevationInMeters has 498134 (85.2%) missing values Missing
maximumElevationInMeters has 574841 (98.3%) missing values Missing
verbatimElevation has 583438 (99.8%) missing values Missing
decimalLatitude has 556694 (95.2%) missing values Missing
decimalLongitude has 556694 (95.2%) missing values Missing
geodeticDatum has 584348 (99.9%) missing values Missing
verbatimLatitude has 561920 (96.1%) missing values Missing
verbatimLongitude has 563009 (96.3%) missing values Missing
verbatimCoordinateSystem has 567398 (97.0%) missing values Missing
georeferenceProtocol has 583454 (99.8%) missing values Missing
identificationQualifier has 584013 (99.9%) missing values Missing
typeStatus has 580729 (99.3%) missing values Missing
identifiedBy has 581316 (99.4%) missing values Missing
infraspecificEpithet has 268452 (45.9%) missing values Missing
taxonRank has 268452 (45.9%) missing values Missing
scientificNameAuthorship has 583567 (99.8%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique
catalogNumber has unique values Unique

Reproduction

Analysis started2025-03-26 20:27:33.806589
Analysis finished2025-03-26 20:27:48.567879
Duration14.76 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct584707
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:48.841774image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters5847070
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584707 ?
Unique (%)100.0%

Sample

1st row1456247698
2nd row1317202804
3rd row1320495121
4th row1320496555
5th row1317204737
ValueCountFrequency (%)
1456247698 1
 
< 0.1%
1317206952 1
 
< 0.1%
1317250051 1
 
< 0.1%
1320499326 1
 
< 0.1%
1320495121 1
 
< 0.1%
1320496555 1
 
< 0.1%
1317204737 1
 
< 0.1%
1317205215 1
 
< 0.1%
1317207003 1
 
< 0.1%
1675766656 1
 
< 0.1%
Other values (584697) 584697
> 99.9%
2025-03-26T16:27:49.205550image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1203203
20.6%
3 890448
15.2%
2 755793
12.9%
9 472464
 
8.1%
0 451528
 
7.7%
8 446732
 
7.6%
7 431317
 
7.4%
5 410299
 
7.0%
4 403528
 
6.9%
6 381758
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5847070
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1203203
20.6%
3 890448
15.2%
2 755793
12.9%
9 472464
 
8.1%
0 451528
 
7.7%
8 446732
 
7.6%
7 431317
 
7.4%
5 410299
 
7.0%
4 403528
 
6.9%
6 381758
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5847070
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1203203
20.6%
3 890448
15.2%
2 755793
12.9%
9 472464
 
8.1%
0 451528
 
7.7%
8 446732
 
7.6%
7 431317
 
7.4%
5 410299
 
7.0%
4 403528
 
6.9%
6 381758
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5847070
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1203203
20.6%
3 890448
15.2%
2 755793
12.9%
9 472464
 
8.1%
0 451528
 
7.7%
8 446732
 
7.6%
7 431317
 
7.4%
5 410299
 
7.0%
4 403528
 
6.9%
6 381758
 
6.5%
Distinct12560
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:49.355335image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11109433
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5296 ?
Unique (%)0.9%

Sample

1st row2024-11-12 09:38:00
2nd row2022-09-22 22:13:00
3rd row2022-09-22 18:19:00
4th row2022-09-22 21:45:00
5th row2022-04-12 14:13:00
ValueCountFrequency (%)
2022-09-22 268427
 
23.0%
2024-09-19 30503
 
2.6%
2022-04-07 28648
 
2.4%
2022-04-11 25208
 
2.2%
2022-04-12 24007
 
2.1%
2022-05-02 15924
 
1.4%
2022-04-29 14924
 
1.3%
2022-06-29 10799
 
0.9%
2022-04-18 9715
 
0.8%
2022-06-08 9587
 
0.8%
Other values (1568) 731672
62.6%
2025-03-26T16:27:49.551618image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 2853297
25.7%
0 2776987
25.0%
- 1169414
10.5%
: 1169414
10.5%
1 801350
 
7.2%
584707
 
5.3%
9 464974
 
4.2%
4 410910
 
3.7%
5 257944
 
2.3%
3 228698
 
2.1%
Other values (3) 391738
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11109433
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 2853297
25.7%
0 2776987
25.0%
- 1169414
10.5%
: 1169414
10.5%
1 801350
 
7.2%
584707
 
5.3%
9 464974
 
4.2%
4 410910
 
3.7%
5 257944
 
2.3%
3 228698
 
2.1%
Other values (3) 391738
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11109433
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 2853297
25.7%
0 2776987
25.0%
- 1169414
10.5%
: 1169414
10.5%
1 801350
 
7.2%
584707
 
5.3%
9 464974
 
4.2%
4 410910
 
3.7%
5 257944
 
2.3%
3 228698
 
2.1%
Other values (3) 391738
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11109433
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 2853297
25.7%
0 2776987
25.0%
- 1169414
10.5%
: 1169414
10.5%
1 801350
 
7.2%
584707
 
5.3%
9 464974
 
4.2%
4 410910
 
3.7%
5 257944
 
2.3%
3 228698
 
2.1%
Other values (3) 391738
 
3.5%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:49.589129image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters16956503
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 584707
100.0%
2025-03-26T16:27:49.664347image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2338828
13.8%
: 2338828
13.8%
l 1754121
 
10.3%
i 1169414
 
6.9%
r 1169414
 
6.9%
c 1169414
 
6.9%
g 584707
 
3.4%
7 584707
 
3.4%
8 584707
 
3.4%
4 584707
 
3.4%
Other values (8) 4677656
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 16956503
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2338828
13.8%
: 2338828
13.8%
l 1754121
 
10.3%
i 1169414
 
6.9%
r 1169414
 
6.9%
c 1169414
 
6.9%
g 584707
 
3.4%
7 584707
 
3.4%
8 584707
 
3.4%
4 584707
 
3.4%
Other values (8) 4677656
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 16956503
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2338828
13.8%
: 2338828
13.8%
l 1754121
 
10.3%
i 1169414
 
6.9%
r 1169414
 
6.9%
c 1169414
 
6.9%
g 584707
 
3.4%
7 584707
 
3.4%
8 584707
 
3.4%
4 584707
 
3.4%
Other values (8) 4677656
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 16956503
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2338828
13.8%
: 2338828
13.8%
l 1754121
 
10.3%
i 1169414
 
6.9%
r 1169414
 
6.9%
c 1169414
 
6.9%
g 584707
 
3.4%
7 584707
 
3.4%
8 584707
 
3.4%
4 584707
 
3.4%
Other values (8) 4677656
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:49.692347image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters26311815
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
2nd rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
3rd rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
4th rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
5th rowurn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893
ValueCountFrequency (%)
urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893 584707
100.0%
2025-03-26T16:27:49.772761image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 3508242
13.3%
d 2923535
11.1%
9 2338828
 
8.9%
- 2338828
 
8.9%
u 1754121
 
6.7%
8 1754121
 
6.7%
2 1754121
 
6.7%
7 1169414
 
4.4%
: 1169414
 
4.4%
c 1169414
 
4.4%
Other values (10) 6431777
24.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26311815
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 3508242
13.3%
d 2923535
11.1%
9 2338828
 
8.9%
- 2338828
 
8.9%
u 1754121
 
6.7%
8 1754121
 
6.7%
2 1754121
 
6.7%
7 1169414
 
4.4%
: 1169414
 
4.4%
c 1169414
 
4.4%
Other values (10) 6431777
24.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26311815
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 3508242
13.3%
d 2923535
11.1%
9 2338828
 
8.9%
- 2338828
 
8.9%
u 1754121
 
6.7%
8 1754121
 
6.7%
2 1754121
 
6.7%
7 1169414
 
4.4%
: 1169414
 
4.4%
c 1169414
 
4.4%
Other values (10) 6431777
24.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26311815
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 3508242
13.3%
d 2923535
11.1%
9 2338828
 
8.9%
- 2338828
 
8.9%
u 1754121
 
6.7%
8 1754121
 
6.7%
2 1754121
 
6.7%
7 1169414
 
4.4%
: 1169414
 
4.4%
c 1169414
 
4.4%
Other values (10) 6431777
24.4%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:49.799497image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2338828
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 584707
100.0%
2025-03-26T16:27:49.876740image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584707
25.0%
S 584707
25.0%
N 584707
25.0%
M 584707
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2338828
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584707
25.0%
S 584707
25.0%
N 584707
25.0%
M 584707
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2338828
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584707
25.0%
S 584707
25.0%
N 584707
25.0%
M 584707
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2338828
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584707
25.0%
S 584707
25.0%
N 584707
25.0%
M 584707
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:49.901740image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters2923535
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBIRDS
2nd rowBIRDS
3rd rowBIRDS
4th rowBIRDS
5th rowBIRDS
ValueCountFrequency (%)
birds 584707
100.0%
2025-03-26T16:27:49.979933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 584707
20.0%
I 584707
20.0%
R 584707
20.0%
D 584707
20.0%
S 584707
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2923535
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 584707
20.0%
I 584707
20.0%
R 584707
20.0%
D 584707
20.0%
S 584707
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2923535
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 584707
20.0%
I 584707
20.0%
R 584707
20.0%
D 584707
20.0%
S 584707
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2923535
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 584707
20.0%
I 584707
20.0%
R 584707
20.0%
D 584707
20.0%
S 584707
20.0%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:50.008932image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11109433
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 584707
33.3%
extant 584707
33.3%
biology 584707
33.3%
2025-03-26T16:27:50.089793image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1169414
 
10.5%
1169414
 
10.5%
t 1169414
 
10.5%
o 1169414
 
10.5%
M 584707
 
5.3%
H 584707
 
5.3%
E 584707
 
5.3%
x 584707
 
5.3%
a 584707
 
5.3%
n 584707
 
5.3%
Other values (5) 2923535
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11109433
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1169414
 
10.5%
1169414
 
10.5%
t 1169414
 
10.5%
o 1169414
 
10.5%
M 584707
 
5.3%
H 584707
 
5.3%
E 584707
 
5.3%
x 584707
 
5.3%
a 584707
 
5.3%
n 584707
 
5.3%
Other values (5) 2923535
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11109433
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1169414
 
10.5%
1169414
 
10.5%
t 1169414
 
10.5%
o 1169414
 
10.5%
M 584707
 
5.3%
H 584707
 
5.3%
E 584707
 
5.3%
x 584707
 
5.3%
a 584707
 
5.3%
n 584707
 
5.3%
Other values (5) 2923535
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11109433
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1169414
 
10.5%
1169414
 
10.5%
t 1169414
 
10.5%
o 1169414
 
10.5%
M 584707
 
5.3%
H 584707
 
5.3%
E 584707
 
5.3%
x 584707
 
5.3%
a 584707
 
5.3%
n 584707
 
5.3%
Other values (5) 2923535
26.3%

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:50.115753image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length17
Min length17

Characters and Unicode

Total characters9940019
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 584707
100.0%
2025-03-26T16:27:50.194376image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2923535
29.4%
r 1169414
 
11.8%
P 584707
 
5.9%
s 584707
 
5.9%
v 584707
 
5.9%
d 584707
 
5.9%
S 584707
 
5.9%
p 584707
 
5.9%
c 584707
 
5.9%
i 584707
 
5.9%
Other values (2) 1169414
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9940019
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2923535
29.4%
r 1169414
 
11.8%
P 584707
 
5.9%
s 584707
 
5.9%
v 584707
 
5.9%
d 584707
 
5.9%
S 584707
 
5.9%
p 584707
 
5.9%
c 584707
 
5.9%
i 584707
 
5.9%
Other values (2) 1169414
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9940019
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2923535
29.4%
r 1169414
 
11.8%
P 584707
 
5.9%
s 584707
 
5.9%
v 584707
 
5.9%
d 584707
 
5.9%
S 584707
 
5.9%
p 584707
 
5.9%
c 584707
 
5.9%
i 584707
 
5.9%
Other values (2) 1169414
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9940019
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2923535
29.4%
r 1169414
 
11.8%
P 584707
 
5.9%
s 584707
 
5.9%
v 584707
 
5.9%
d 584707
 
5.9%
S 584707
 
5.9%
p 584707
 
5.9%
c 584707
 
5.9%
i 584707
 
5.9%
Other values (2) 1169414
 
11.8%

occurrenceID
Text

Unique 

Distinct584707
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:50.423849image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters36836541
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584707 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/391a09ab4-f109-4ff9-af63-3d4797c46473
2nd rowhttp://n2t.net/ark:/65665/300045ed6-5dc8-4eb3-86bb-81ed02d32b85
3rd rowhttp://n2t.net/ark:/65665/391a47809-4a1b-48d8-99aa-5173a56aef42
4th rowhttp://n2t.net/ark:/65665/391b4298d-68d5-4e44-b737-c9d162cbaac0
5th rowhttp://n2t.net/ark:/65665/30019a910-c153-4a5f-b16e-929dbdf511f2
ValueCountFrequency (%)
http://n2t.net/ark:/65665/391a09ab4-f109-4ff9-af63-3d4797c46473 1
 
< 0.1%
http://n2t.net/ark:/65665/300330e32-bc48-410d-86a4-0d49d5c2767d 1
 
< 0.1%
http://n2t.net/ark:/65665/3021bf070-e046-4ad7-a740-01956780da0b 1
 
< 0.1%
http://n2t.net/ark:/65665/391d4c6fc-7da2-4895-be38-1a0c34ec896f 1
 
< 0.1%
http://n2t.net/ark:/65665/391a47809-4a1b-48d8-99aa-5173a56aef42 1
 
< 0.1%
http://n2t.net/ark:/65665/391b4298d-68d5-4e44-b737-c9d162cbaac0 1
 
< 0.1%
http://n2t.net/ark:/65665/30019a910-c153-4a5f-b16e-929dbdf511f2 1
 
< 0.1%
http://n2t.net/ark:/65665/3001f958e-8f35-48cc-a24c-2f132e1cbf9d 1
 
< 0.1%
http://n2t.net/ark:/65665/3003407f8-cdfc-4365-b3af-fa5a411ac2af 1
 
< 0.1%
http://n2t.net/ark:/65665/30090a564-0484-4070-927a-bdefd74094ea 1
 
< 0.1%
Other values (584697) 584697
> 99.9%
2025-03-26T16:27:50.752323image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 2923535
 
7.9%
6 2852600
 
7.7%
- 2338828
 
6.3%
t 2338828
 
6.3%
5 2266123
 
6.2%
a 1827694
 
5.0%
2 1681823
 
4.6%
3 1680834
 
4.6%
e 1680511
 
4.6%
4 1680316
 
4.6%
Other values (16) 15565449
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36836541
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 2923535
 
7.9%
6 2852600
 
7.7%
- 2338828
 
6.3%
t 2338828
 
6.3%
5 2266123
 
6.2%
a 1827694
 
5.0%
2 1681823
 
4.6%
3 1680834
 
4.6%
e 1680511
 
4.6%
4 1680316
 
4.6%
Other values (16) 15565449
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36836541
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 2923535
 
7.9%
6 2852600
 
7.7%
- 2338828
 
6.3%
t 2338828
 
6.3%
5 2266123
 
6.2%
a 1827694
 
5.0%
2 1681823
 
4.6%
3 1680834
 
4.6%
e 1680511
 
4.6%
4 1680316
 
4.6%
Other values (16) 15565449
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36836541
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 2923535
 
7.9%
6 2852600
 
7.7%
- 2338828
 
6.3%
t 2338828
 
6.3%
5 2266123
 
6.2%
a 1827694
 
5.0%
2 1681823
 
4.6%
3 1680834
 
4.6%
e 1680511
 
4.6%
4 1680316
 
4.6%
Other values (16) 15565449
42.3%

catalogNumber
Text

Unique 

Distinct584707
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:51.098068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length11
Median length11
Mean length10.92078768
Min length6

Characters and Unicode

Total characters6385461
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique584707 ?
Unique (%)100.0%

Sample

1st rowUSNM 361680
2nd rowUSNM 354639
3rd rowUSNM 445621
4th rowUSNM 476734
5th rowUSNM 303211
ValueCountFrequency (%)
usnm 584707
50.0%
569026 1
 
< 0.1%
610657 1
 
< 0.1%
95690 1
 
< 0.1%
445621 1
 
< 0.1%
476734 1
 
< 0.1%
303211 1
 
< 0.1%
640577 1
 
< 0.1%
154936 1
 
< 0.1%
571285 1
 
< 0.1%
Other values (584698) 584698
50.0%
2025-03-26T16:27:51.499741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 584707
 
9.2%
N 584707
 
9.2%
M 584707
 
9.2%
584707
 
9.2%
S 584707
 
9.2%
3 396675
 
6.2%
4 396238
 
6.2%
5 388261
 
6.1%
1 387482
 
6.1%
2 382752
 
6.0%
Other values (7) 1510518
23.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6385461
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 584707
 
9.2%
N 584707
 
9.2%
M 584707
 
9.2%
584707
 
9.2%
S 584707
 
9.2%
3 396675
 
6.2%
4 396238
 
6.2%
5 388261
 
6.1%
1 387482
 
6.1%
2 382752
 
6.0%
Other values (7) 1510518
23.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6385461
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 584707
 
9.2%
N 584707
 
9.2%
M 584707
 
9.2%
584707
 
9.2%
S 584707
 
9.2%
3 396675
 
6.2%
4 396238
 
6.2%
5 388261
 
6.1%
1 387482
 
6.1%
2 382752
 
6.0%
Other values (7) 1510518
23.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6385461
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 584707
 
9.2%
N 584707
 
9.2%
M 584707
 
9.2%
584707
 
9.2%
S 584707
 
9.2%
3 396675
 
6.2%
4 396238
 
6.2%
5 388261
 
6.1%
1 387482
 
6.1%
2 382752
 
6.0%
Other values (7) 1510518
23.7%

recordNumber
Text

Missing 

Distinct4
Distinct (%)3.4%
Missing584589
Missing (%)> 99.9%
Memory size4.5 MiB
2025-03-26T16:27:51.543756image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.059322034
Min length1

Characters and Unicode

Total characters125
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)2.5%

Sample

1st rowl
2nd rowl
3rd rowl
4th rowl
5th rowl
ValueCountFrequency (%)
l 115
97.5%
sta 1
 
0.8%
riley 1
 
0.8%
du 1
 
0.8%
2025-03-26T16:27:51.633610image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 116
92.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
d 1
 
0.8%
u 1
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 125
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 116
92.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
d 1
 
0.8%
u 1
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 125
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 116
92.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
d 1
 
0.8%
u 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 125
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 116
92.8%
s 1
 
0.8%
t 1
 
0.8%
a 1
 
0.8%
r 1
 
0.8%
i 1
 
0.8%
e 1
 
0.8%
y 1
 
0.8%
d 1
 
0.8%
u 1
 
0.8%

recordedBy
Text

Missing 

Distinct13258
Distinct (%)2.3%
Missing7169
Missing (%)1.2%
Memory size4.5 MiB
2025-03-26T16:27:51.767701image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length55
Mean length11.76067722
Min length1

Characters and Unicode

Total characters6792238
Distinct characters65
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6178 ?
Unique (%)1.1%

Sample

1st rowA. Wetmore
2nd rowS. Danforth
3rd rowE. Haydock
4th rowA. Wetmore
5th rowA. Sowerby
ValueCountFrequency (%)
a 64588
 
4.8%
j 60299
 
4.5%
e 58461
 
4.4%
56517
 
4.2%
w 52991
 
4.0%
h 41943
 
3.1%
m 37813
 
2.8%
c 37337
 
2.8%
t 32508
 
2.4%
wetmore 32381
 
2.4%
Other values (7407) 863569
64.5%
2025-03-26T16:27:52.085824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
760869
 
11.2%
. 559091
 
8.2%
e 547371
 
8.1%
r 485455
 
7.1%
o 389538
 
5.7%
n 353979
 
5.2%
a 303518
 
4.5%
l 299850
 
4.4%
i 264165
 
3.9%
t 245224
 
3.6%
Other values (55) 2583178
38.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6792238
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
760869
 
11.2%
. 559091
 
8.2%
e 547371
 
8.1%
r 485455
 
7.1%
o 389538
 
5.7%
n 353979
 
5.2%
a 303518
 
4.5%
l 299850
 
4.4%
i 264165
 
3.9%
t 245224
 
3.6%
Other values (55) 2583178
38.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6792238
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
760869
 
11.2%
. 559091
 
8.2%
e 547371
 
8.1%
r 485455
 
7.1%
o 389538
 
5.7%
n 353979
 
5.2%
a 303518
 
4.5%
l 299850
 
4.4%
i 264165
 
3.9%
t 245224
 
3.6%
Other values (55) 2583178
38.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6792238
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
760869
 
11.2%
. 559091
 
8.2%
e 547371
 
8.1%
r 485455
 
7.1%
o 389538
 
5.7%
n 353979
 
5.2%
a 303518
 
4.5%
l 299850
 
4.4%
i 264165
 
3.9%
t 245224
 
3.6%
Other values (55) 2583178
38.0%
Distinct49
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:27:52.128438image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length1
Mean length1.001168106
Min length1

Characters and Unicode

Total characters585390
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 558424
95.5%
2 6799
 
1.2%
4 6794
 
1.2%
3 6435
 
1.1%
5 3136
 
0.5%
6 1204
 
0.2%
7 608
 
0.1%
8 374
 
0.1%
9 251
 
< 0.1%
10 169
 
< 0.1%
Other values (39) 513
 
0.1%
2025-03-26T16:27:52.219453image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 559167
95.5%
2 6944
 
1.2%
4 6855
 
1.2%
3 6513
 
1.1%
5 3191
 
0.5%
6 1239
 
0.2%
7 631
 
0.1%
8 397
 
0.1%
9 270
 
< 0.1%
0 183
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 585390
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 559167
95.5%
2 6944
 
1.2%
4 6855
 
1.2%
3 6513
 
1.1%
5 3191
 
0.5%
6 1239
 
0.2%
7 631
 
0.1%
8 397
 
0.1%
9 270
 
< 0.1%
0 183
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 585390
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 559167
95.5%
2 6944
 
1.2%
4 6855
 
1.2%
3 6513
 
1.1%
5 3191
 
0.5%
6 1239
 
0.2%
7 631
 
0.1%
8 397
 
0.1%
9 270
 
< 0.1%
0 183
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 585390
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 559167
95.5%
2 6944
 
1.2%
4 6855
 
1.2%
3 6513
 
1.1%
5 3191
 
0.5%
6 1239
 
0.2%
7 631
 
0.1%
8 397
 
0.1%
9 270
 
< 0.1%
0 183
 
< 0.1%

sex
Text

Distinct6
Distinct (%)< 0.1%
Missing2
Missing (%)< 0.1%
Memory size4.5 MiB
2025-03-26T16:27:52.248452image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.236700558
Min length4

Characters and Unicode

Total characters3061925
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMale
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale
ValueCountFrequency (%)
male 279290
47.8%
female 193140
33.0%
unknown 112275
19.2%
2025-03-26T16:27:52.331694image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 664350
21.7%
a 471566
15.4%
l 471566
15.4%
n 336825
11.0%
M 279646
9.1%
F 193140
 
6.3%
m 192784
 
6.3%
k 112275
 
3.7%
o 112275
 
3.7%
w 112275
 
3.7%
Other values (5) 115223
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3061925
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 664350
21.7%
a 471566
15.4%
l 471566
15.4%
n 336825
11.0%
M 279646
9.1%
F 193140
 
6.3%
m 192784
 
6.3%
k 112275
 
3.7%
o 112275
 
3.7%
w 112275
 
3.7%
Other values (5) 115223
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3061925
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 664350
21.7%
a 471566
15.4%
l 471566
15.4%
n 336825
11.0%
M 279646
9.1%
F 193140
 
6.3%
m 192784
 
6.3%
k 112275
 
3.7%
o 112275
 
3.7%
w 112275
 
3.7%
Other values (5) 115223
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3061925
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 664350
21.7%
a 471566
15.4%
l 471566
15.4%
n 336825
11.0%
M 279646
9.1%
F 193140
 
6.3%
m 192784
 
6.3%
k 112275
 
3.7%
o 112275
 
3.7%
w 112275
 
3.7%
Other values (5) 115223
 
3.8%

lifeStage
Text

Missing 

Distinct14
Distinct (%)< 0.1%
Missing459596
Missing (%)78.6%
Memory size4.5 MiB
2025-03-26T16:27:52.360201image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length5
Mean length5.961146502
Min length5

Characters and Unicode

Total characters745805
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowImmature
2nd rowImmature
3rd rowImmature
4th rowAdult
5th rowAdult
ValueCountFrequency (%)
adult 81116
64.8%
immature 27827
 
22.2%
juvenile 10776
 
8.6%
chick 3715
 
3.0%
subadult 1382
 
1.1%
embryo 292
 
0.2%
young 2
 
< 0.1%
nestling 1
 
< 0.1%
2025-03-26T16:27:52.442728image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
u 122485
16.4%
t 110326
14.8%
l 93275
12.5%
d 82498
11.1%
A 81092
10.9%
m 55946
7.5%
e 49381
6.6%
a 29233
 
3.9%
r 28119
 
3.8%
I 27824
 
3.7%
Other values (17) 65626
8.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 745805
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
u 122485
16.4%
t 110326
14.8%
l 93275
12.5%
d 82498
11.1%
A 81092
10.9%
m 55946
7.5%
e 49381
6.6%
a 29233
 
3.9%
r 28119
 
3.8%
I 27824
 
3.7%
Other values (17) 65626
8.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 745805
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
u 122485
16.4%
t 110326
14.8%
l 93275
12.5%
d 82498
11.1%
A 81092
10.9%
m 55946
7.5%
e 49381
6.6%
a 29233
 
3.9%
r 28119
 
3.8%
I 27824
 
3.7%
Other values (17) 65626
8.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 745805
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
u 122485
16.4%
t 110326
14.8%
l 93275
12.5%
d 82498
11.1%
A 81092
10.9%
m 55946
7.5%
e 49381
6.6%
a 29233
 
3.9%
r 28119
 
3.8%
I 27824
 
3.7%
Other values (17) 65626
8.8%
Distinct133
Distinct (%)< 0.1%
Missing6
Missing (%)< 0.1%
Memory size4.5 MiB
2025-03-26T16:27:52.473233image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length76
Median length11
Mean length11.71026217
Min length6

Characters and Unicode

Total characters6847002
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)< 0.1%

Sample

1st rowSkin: Whole
2nd rowSkin: Whole
3rd rowSkin: Whole
4th rowSkin: Whole
5th rowSkin: Whole
ValueCountFrequency (%)
whole 535523
45.8%
skin 470498
40.2%
skeleton 58563
 
5.0%
egg(s 33064
 
2.8%
fluid 32615
 
2.8%
partial 24548
 
2.1%
nest(s 4794
 
0.4%
feather(s 4785
 
0.4%
mounted 1952
 
0.2%
clutch 967
 
0.1%
Other values (7) 2530
 
0.2%
2025-03-26T16:27:52.572859image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 671477
9.8%
l 654105
9.6%
o 596038
8.7%
585138
8.5%
: 563008
8.2%
h 541275
7.9%
W 535522
7.8%
n 532203
7.8%
i 529463
7.7%
S 529415
7.7%
Other values (21) 1109358
16.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6847002
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 671477
9.8%
l 654105
9.6%
o 596038
8.7%
585138
8.5%
: 563008
8.2%
h 541275
7.9%
W 535522
7.8%
n 532203
7.8%
i 529463
7.7%
S 529415
7.7%
Other values (21) 1109358
16.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6847002
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 671477
9.8%
l 654105
9.6%
o 596038
8.7%
585138
8.5%
: 563008
8.2%
h 541275
7.9%
W 535522
7.8%
n 532203
7.8%
i 529463
7.7%
S 529415
7.7%
Other values (21) 1109358
16.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6847002
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 671477
9.8%
l 654105
9.6%
o 596038
8.7%
585138
8.5%
: 563008
8.2%
h 541275
7.9%
W 535522
7.8%
n 532203
7.8%
i 529463
7.7%
S 529415
7.7%
Other values (21) 1109358
16.2%

associatedMedia
Text

Missing 

Distinct38231
Distinct (%)6.8%
Missing26145
Missing (%)4.5%
Memory size4.5 MiB
2025-03-26T16:27:52.642212image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1279
Median length49
Mean length49.9494792
Min length48

Characters and Unicode

Total characters27899881
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11682 ?
Unique (%)2.1%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=15821224
2nd rowhttps://collections.nmnh.si.edu/media/?i=15821506
3rd rowhttps://collections.nmnh.si.edu/media/?i=15815209
4th rowhttps://collections.nmnh.si.edu/media/?i=15813738
5th rowhttps://collections.nmnh.si.edu/media/?i=15824827
ValueCountFrequency (%)
https://collections.nmnh.si.edu/media/?i=15806683 99
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15817157 98
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15840942 63
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15840941 63
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15840951 63
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=7010826 59
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15840950 54
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15811485 49
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15824469 48
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=15840962 46
 
< 0.1%
Other values (79555) 611176
99.9%
2025-03-26T16:27:52.802516image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 2234248
 
8.0%
/ 2234248
 
8.0%
t 1675686
 
6.0%
s 1675686
 
6.0%
. 1675686
 
6.0%
n 1675686
 
6.0%
e 1675686
 
6.0%
h 1117124
 
4.0%
d 1117124
 
4.0%
m 1117124
 
4.0%
Other values (21) 11701583
41.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27899881
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 2234248
 
8.0%
/ 2234248
 
8.0%
t 1675686
 
6.0%
s 1675686
 
6.0%
. 1675686
 
6.0%
n 1675686
 
6.0%
e 1675686
 
6.0%
h 1117124
 
4.0%
d 1117124
 
4.0%
m 1117124
 
4.0%
Other values (21) 11701583
41.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27899881
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 2234248
 
8.0%
/ 2234248
 
8.0%
t 1675686
 
6.0%
s 1675686
 
6.0%
. 1675686
 
6.0%
n 1675686
 
6.0%
e 1675686
 
6.0%
h 1117124
 
4.0%
d 1117124
 
4.0%
m 1117124
 
4.0%
Other values (21) 11701583
41.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27899881
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 2234248
 
8.0%
/ 2234248
 
8.0%
t 1675686
 
6.0%
s 1675686
 
6.0%
. 1675686
 
6.0%
n 1675686
 
6.0%
e 1675686
 
6.0%
h 1117124
 
4.0%
d 1117124
 
4.0%
m 1117124
 
4.0%
Other values (21) 11701583
41.9%

associatedSequences
Text

Missing 

Distinct4430
Distinct (%)98.7%
Missing580220
Missing (%)99.2%
Memory size4.5 MiB
2025-03-26T16:27:52.846647image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12558
Median length49
Mean length129.0780031
Min length49

Characters and Unicode

Total characters579173
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4421 ?
Unique (%)98.5%

Sample

1st rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JF499076
2nd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ174743
3rd rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ176095
4th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JF498765
5th rowhttps://www.ncbi.nlm.nih.gov/gquery?term=JQ175426
ValueCountFrequency (%)
https://www.ncbi.nlm.nih.gov/gquery?term=prjna521985 34
 
0.8%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273835 10
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273864 8
 
0.2%
https://www.ncbi.nlm.nih.gov/gquery?term=ay273832 3
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj207364 3
 
0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=dq433197 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj207374 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=mh778417 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=fj207379 2
 
< 0.1%
https://www.ncbi.nlm.nih.gov/gquery?term=jq174915 1
 
< 0.1%
Other values (4420) 4420
98.5%
2025-03-26T16:27:52.949556image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
w 34770
 
6.0%
n 34770
 
6.0%
t 34770
 
6.0%
h 23180
 
4.0%
r 23180
 
4.0%
e 23180
 
4.0%
i 23180
 
4.0%
m 23180
 
4.0%
Other values (53) 277832
48.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 579173
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
w 34770
 
6.0%
n 34770
 
6.0%
t 34770
 
6.0%
h 23180
 
4.0%
r 23180
 
4.0%
e 23180
 
4.0%
i 23180
 
4.0%
m 23180
 
4.0%
Other values (53) 277832
48.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 579173
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
w 34770
 
6.0%
n 34770
 
6.0%
t 34770
 
6.0%
h 23180
 
4.0%
r 23180
 
4.0%
e 23180
 
4.0%
i 23180
 
4.0%
m 23180
 
4.0%
Other values (53) 277832
48.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 579173
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 46361
 
8.0%
/ 34770
 
6.0%
w 34770
 
6.0%
n 34770
 
6.0%
t 34770
 
6.0%
h 23180
 
4.0%
r 23180
 
4.0%
e 23180
 
4.0%
i 23180
 
4.0%
m 23180
 
4.0%
Other values (53) 277832
48.0%

occurrenceRemarks
Text

Missing 

Distinct7441
Distinct (%)60.4%
Missing572381
Missing (%)97.9%
Memory size4.5 MiB
2025-03-26T16:27:53.079622image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6354
Median length553
Mean length50.68132403
Min length1

Characters and Unicode

Total characters624698
Distinct characters102
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6461 ?
Unique (%)52.4%

Sample

1st rowa skulking bird
2nd rowTo School Coll Oct 1976; cage bird
3rd rowLeg tag T056
4th rowfall plumage
5th rowBreeding
ValueCountFrequency (%)
of 4622
 
4.3%
in 2355
 
2.2%
as 2210
 
2.1%
the 2145
 
2.0%
usnm 2055
 
1.9%
tag 1762
 
1.7%
specimens 1534
 
1.4%
cataloged 1516
 
1.4%
1424
 
1.3%
originally 1393
 
1.3%
Other values (10814) 85289
80.2%
2025-03-26T16:27:53.296759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
93979
15.0%
e 51966
 
8.3%
a 38104
 
6.1%
n 35174
 
5.6%
o 34197
 
5.5%
i 32806
 
5.3%
t 32490
 
5.2%
s 26732
 
4.3%
r 26063
 
4.2%
l 23057
 
3.7%
Other values (92) 230130
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 624698
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
93979
15.0%
e 51966
 
8.3%
a 38104
 
6.1%
n 35174
 
5.6%
o 34197
 
5.5%
i 32806
 
5.3%
t 32490
 
5.2%
s 26732
 
4.3%
r 26063
 
4.2%
l 23057
 
3.7%
Other values (92) 230130
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 624698
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
93979
15.0%
e 51966
 
8.3%
a 38104
 
6.1%
n 35174
 
5.6%
o 34197
 
5.5%
i 32806
 
5.3%
t 32490
 
5.2%
s 26732
 
4.3%
r 26063
 
4.2%
l 23057
 
3.7%
Other values (92) 230130
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 624698
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
93979
15.0%
e 51966
 
8.3%
a 38104
 
6.1%
n 35174
 
5.6%
o 34197
 
5.5%
i 32806
 
5.3%
t 32490
 
5.2%
s 26732
 
4.3%
r 26063
 
4.2%
l 23057
 
3.7%
Other values (92) 230130
36.8%

eventDate
Text

Missing 

Distinct51276
Distinct (%)9.4%
Missing41219
Missing (%)7.0%
Memory size4.5 MiB
2025-03-26T16:27:53.448070image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length10
Mean length9.765251487
Min length4

Characters and Unicode

Total characters5307297
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8025 ?
Unique (%)1.5%

Sample

1st row1940-11-12
2nd row1926-07-31
3rd row1951-01-01
4th row1962-03-02
5th row1924-04-09
ValueCountFrequency (%)
1865 620
 
0.1%
1877 533
 
0.1%
1966 478
 
0.1%
1926 419
 
0.1%
1939-07 366
 
0.1%
1937 360
 
0.1%
1936 280
 
0.1%
1884 276
 
0.1%
1888 253
 
< 0.1%
1881 251
 
< 0.1%
Other values (51266) 539654
99.3%
2025-03-26T16:27:53.665108image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1043084
19.7%
1 1033040
19.5%
0 808931
15.2%
9 612120
11.5%
2 401501
 
7.6%
8 309125
 
5.8%
6 249509
 
4.7%
3 225549
 
4.2%
5 223647
 
4.2%
4 216201
 
4.1%
Other values (5) 184590
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5307297
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 1043084
19.7%
1 1033040
19.5%
0 808931
15.2%
9 612120
11.5%
2 401501
 
7.6%
8 309125
 
5.8%
6 249509
 
4.7%
3 225549
 
4.2%
5 223647
 
4.2%
4 216201
 
4.1%
Other values (5) 184590
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5307297
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 1043084
19.7%
1 1033040
19.5%
0 808931
15.2%
9 612120
11.5%
2 401501
 
7.6%
8 309125
 
5.8%
6 249509
 
4.7%
3 225549
 
4.2%
5 223647
 
4.2%
4 216201
 
4.1%
Other values (5) 184590
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5307297
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 1043084
19.7%
1 1033040
19.5%
0 808931
15.2%
9 612120
11.5%
2 401501
 
7.6%
8 309125
 
5.8%
6 249509
 
4.7%
3 225549
 
4.2%
5 223647
 
4.2%
4 216201
 
4.1%
Other values (5) 184590
 
3.5%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing55198
Missing (%)9.4%
Memory size4.5 MiB
2025-03-26T16:27:53.812406image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.722354105
Min length1

Characters and Unicode

Total characters1441511
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row317
2nd row212
3rd row1
4th row61
5th row100
ValueCountFrequency (%)
151 3517
 
0.7%
181 3363
 
0.6%
120 2982
 
0.6%
212 2839
 
0.5%
152 2631
 
0.5%
140 2507
 
0.5%
141 2480
 
0.5%
90 2458
 
0.5%
134 2427
 
0.5%
135 2416
 
0.5%
Other values (356) 501889
94.8%
2025-03-26T16:27:54.007873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 306709
21.3%
2 236657
16.4%
3 179620
12.5%
5 113295
 
7.9%
4 112452
 
7.8%
6 107214
 
7.4%
7 97836
 
6.8%
0 96831
 
6.7%
8 95847
 
6.6%
9 95050
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1441511
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 306709
21.3%
2 236657
16.4%
3 179620
12.5%
5 113295
 
7.9%
4 112452
 
7.8%
6 107214
 
7.4%
7 97836
 
6.8%
0 96831
 
6.7%
8 95847
 
6.6%
9 95050
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1441511
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 306709
21.3%
2 236657
16.4%
3 179620
12.5%
5 113295
 
7.9%
4 112452
 
7.8%
6 107214
 
7.4%
7 97836
 
6.8%
0 96831
 
6.7%
8 95847
 
6.6%
9 95050
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1441511
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 306709
21.3%
2 236657
16.4%
3 179620
12.5%
5 113295
 
7.9%
4 112452
 
7.8%
6 107214
 
7.4%
7 97836
 
6.8%
0 96831
 
6.7%
8 95847
 
6.6%
9 95050
 
6.6%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing55020
Missing (%)9.4%
Memory size4.5 MiB
2025-03-26T16:27:54.148338image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.722186876
Min length1

Characters and Unicode

Total characters1441907
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row317
2nd row212
3rd row1
4th row61
5th row100
ValueCountFrequency (%)
151 3513
 
0.7%
181 3367
 
0.6%
120 2999
 
0.6%
212 2842
 
0.5%
152 2637
 
0.5%
59 2554
 
0.5%
140 2509
 
0.5%
141 2480
 
0.5%
90 2455
 
0.5%
134 2426
 
0.5%
Other values (356) 501905
94.8%
2025-03-26T16:27:54.349306image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 306742
21.3%
2 236666
16.4%
3 179638
12.5%
5 113379
 
7.9%
4 112487
 
7.8%
6 107276
 
7.4%
7 97814
 
6.8%
0 96849
 
6.7%
8 95849
 
6.6%
9 95207
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1441907
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 306742
21.3%
2 236666
16.4%
3 179638
12.5%
5 113379
 
7.9%
4 112487
 
7.8%
6 107276
 
7.4%
7 97814
 
6.8%
0 96849
 
6.7%
8 95849
 
6.6%
9 95207
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1441907
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 306742
21.3%
2 236666
16.4%
3 179638
12.5%
5 113379
 
7.9%
4 112487
 
7.8%
6 107276
 
7.4%
7 97814
 
6.8%
0 96849
 
6.7%
8 95849
 
6.6%
9 95207
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1441907
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 306742
21.3%
2 236666
16.4%
3 179638
12.5%
5 113379
 
7.9%
4 112487
 
7.8%
6 107276
 
7.4%
7 97814
 
6.8%
0 96849
 
6.7%
8 95849
 
6.6%
9 95207
 
6.6%

year
Text

Missing 

Distinct204
Distinct (%)< 0.1%
Missing41219
Missing (%)7.0%
Memory size4.5 MiB
2025-03-26T16:27:54.472727image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2173952
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row1940
2nd row1926
3rd row1951
4th row1962
5th row1924
ValueCountFrequency (%)
1965 14461
 
2.7%
1964 13002
 
2.4%
1966 10904
 
2.0%
1912 9422
 
1.7%
1911 8200
 
1.5%
1949 8030
 
1.5%
1923 7875
 
1.4%
1950 6975
 
1.3%
1967 6969
 
1.3%
1892 6943
 
1.3%
Other values (194) 450707
82.9%
2025-03-26T16:27:54.643315image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 642326
29.5%
9 525063
24.2%
8 217866
 
10.0%
6 138260
 
6.4%
0 135789
 
6.2%
2 113236
 
5.2%
4 110564
 
5.1%
5 102870
 
4.7%
3 100932
 
4.6%
7 87046
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2173952
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 642326
29.5%
9 525063
24.2%
8 217866
 
10.0%
6 138260
 
6.4%
0 135789
 
6.2%
2 113236
 
5.2%
4 110564
 
5.1%
5 102870
 
4.7%
3 100932
 
4.6%
7 87046
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2173952
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 642326
29.5%
9 525063
24.2%
8 217866
 
10.0%
6 138260
 
6.4%
0 135789
 
6.2%
2 113236
 
5.2%
4 110564
 
5.1%
5 102870
 
4.7%
3 100932
 
4.6%
7 87046
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2173952
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 642326
29.5%
9 525063
24.2%
8 217866
 
10.0%
6 138260
 
6.4%
0 135789
 
6.2%
2 113236
 
5.2%
4 110564
 
5.1%
5 102870
 
4.7%
3 100932
 
4.6%
7 87046
 
4.0%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing53375
Missing (%)9.1%
Memory size4.5 MiB
2025-03-26T16:27:54.684821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.178987902
Min length1

Characters and Unicode

Total characters626434
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row7
3rd row1
4th row3
5th row4
ValueCountFrequency (%)
5 70395
13.2%
6 61194
11.5%
4 54203
10.2%
3 50572
9.5%
7 46981
8.8%
2 40501
7.6%
8 39926
7.5%
9 37783
7.1%
10 35529
6.7%
1 34675
6.5%
Other values (2) 59573
11.2%
2025-03-26T16:27:54.770892image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 160577
25.6%
5 70395
11.2%
2 69274
11.1%
6 61194
 
9.8%
4 54203
 
8.7%
3 50572
 
8.1%
7 46981
 
7.5%
8 39926
 
6.4%
9 37783
 
6.0%
0 35529
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 626434
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 160577
25.6%
5 70395
11.2%
2 69274
11.1%
6 61194
 
9.8%
4 54203
 
8.7%
3 50572
 
8.1%
7 46981
 
7.5%
8 39926
 
6.4%
9 37783
 
6.0%
0 35529
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 626434
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 160577
25.6%
5 70395
11.2%
2 69274
11.1%
6 61194
 
9.8%
4 54203
 
8.7%
3 50572
 
8.1%
7 46981
 
7.5%
8 39926
 
6.4%
9 37783
 
6.0%
0 35529
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 626434
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 160577
25.6%
5 70395
11.2%
2 69274
11.1%
6 61194
 
9.8%
4 54203
 
8.7%
3 50572
 
8.1%
7 46981
 
7.5%
8 39926
 
6.4%
9 37783
 
6.0%
0 35529
 
5.7%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing74043
Missing (%)12.7%
Memory size4.5 MiB
2025-03-26T16:27:54.813614image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.707437767
Min length1

Characters and Unicode

Total characters871927
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row31
3rd row1
4th row2
5th row9
ValueCountFrequency (%)
20 17990
 
3.5%
10 17960
 
3.5%
8 17689
 
3.5%
15 17688
 
3.5%
12 17472
 
3.4%
21 17472
 
3.4%
24 17323
 
3.4%
4 17162
 
3.4%
22 17160
 
3.4%
16 17139
 
3.4%
Other values (21) 335609
65.7%
2025-03-26T16:27:54.911661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 228841
26.2%
2 218183
25.0%
3 73786
 
8.5%
4 51253
 
5.9%
8 51036
 
5.9%
0 50857
 
5.8%
5 50239
 
5.8%
6 49856
 
5.7%
7 49524
 
5.7%
9 48352
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 871927
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 228841
26.2%
2 218183
25.0%
3 73786
 
8.5%
4 51253
 
5.9%
8 51036
 
5.9%
0 50857
 
5.8%
5 50239
 
5.8%
6 49856
 
5.7%
7 49524
 
5.7%
9 48352
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 871927
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 228841
26.2%
2 218183
25.0%
3 73786
 
8.5%
4 51253
 
5.9%
8 51036
 
5.9%
0 50857
 
5.8%
5 50239
 
5.8%
6 49856
 
5.7%
7 49524
 
5.7%
9 48352
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 871927
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 228841
26.2%
2 218183
25.0%
3 73786
 
8.5%
4 51253
 
5.9%
8 51036
 
5.9%
0 50857
 
5.8%
5 50239
 
5.8%
6 49856
 
5.7%
7 49524
 
5.7%
9 48352
 
5.5%

verbatimEventDate
Text

Missing 

Distinct44000
Distinct (%)12.6%
Missing235551
Missing (%)40.3%
Memory size4.5 MiB
2025-03-26T16:27:55.035697image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length11
Mean length10.64070788
Min length1

Characters and Unicode

Total characters3715267
Distinct characters77
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10314 ?
Unique (%)3.0%

Sample

1st row12 Nov 1940
2nd row31 Jul 1926
3rd row1 Jan 1951
4th row2 Mar 1962
5th row10 Feb 1971
ValueCountFrequency (%)
149889
 
14.3%
may 43235
 
4.1%
jun 37603
 
3.6%
apr 31574
 
3.0%
mar 27302
 
2.6%
jul 27210
 
2.6%
aug 23687
 
2.3%
feb 21868
 
2.1%
sep 21169
 
2.0%
jan 18183
 
1.7%
Other values (728) 644670
61.6%
2025-03-26T16:27:55.301026image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
697234
18.8%
1 503508
13.6%
- 381786
 
10.3%
9 327437
 
8.8%
2 174522
 
4.7%
8 174211
 
4.7%
6 106903
 
2.9%
3 99639
 
2.7%
4 93970
 
2.5%
a 89433
 
2.4%
Other values (67) 1066624
28.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3715267
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
697234
18.8%
1 503508
13.6%
- 381786
 
10.3%
9 327437
 
8.8%
2 174522
 
4.7%
8 174211
 
4.7%
6 106903
 
2.9%
3 99639
 
2.7%
4 93970
 
2.5%
a 89433
 
2.4%
Other values (67) 1066624
28.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3715267
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
697234
18.8%
1 503508
13.6%
- 381786
 
10.3%
9 327437
 
8.8%
2 174522
 
4.7%
8 174211
 
4.7%
6 106903
 
2.9%
3 99639
 
2.7%
4 93970
 
2.5%
a 89433
 
2.4%
Other values (67) 1066624
28.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3715267
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
697234
18.8%
1 503508
13.6%
- 381786
 
10.3%
9 327437
 
8.8%
2 174522
 
4.7%
8 174211
 
4.7%
6 106903
 
2.9%
3 99639
 
2.7%
4 93970
 
2.5%
a 89433
 
2.4%
Other values (67) 1066624
28.7%

habitat
Text

Missing 

Distinct4924
Distinct (%)28.6%
Missing567499
Missing (%)97.1%
Memory size4.5 MiB
2025-03-26T16:27:55.434901image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length191
Median length141
Mean length27.12441887
Min length3

Characters and Unicode

Total characters466757
Distinct characters82
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3480 ?
Unique (%)20.2%

Sample

1st row500 m wide valley with mixed riparian forest (Salix, Populus, Betula, Larix, etc.), wet meadow on terrace, pure Larix forest on slopes with some Betula along streams and lower edges of slopes
2nd rowAcacia thorn veldt with aloes and surface dolomite stones
3rd rowbrown rice fields
4th rowstony hillls, open acacia scrub, aloes
5th rowin woods along dry creek bed
ValueCountFrequency (%)
forest 6854
 
9.3%
with 2343
 
3.2%
open 1915
 
2.6%
of 1628
 
2.2%
in 1548
 
2.1%
and 1461
 
2.0%
scrub 1279
 
1.7%
edge 1213
 
1.7%
944
 
1.3%
on 919
 
1.3%
Other values (2525) 53396
72.6%
2025-03-26T16:27:55.656467image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56292
 
12.1%
e 41805
 
9.0%
o 33542
 
7.2%
a 33125
 
7.1%
r 31674
 
6.8%
s 31661
 
6.8%
t 25355
 
5.4%
n 24791
 
5.3%
i 21498
 
4.6%
l 17708
 
3.8%
Other values (72) 149306
32.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 466757
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
56292
 
12.1%
e 41805
 
9.0%
o 33542
 
7.2%
a 33125
 
7.1%
r 31674
 
6.8%
s 31661
 
6.8%
t 25355
 
5.4%
n 24791
 
5.3%
i 21498
 
4.6%
l 17708
 
3.8%
Other values (72) 149306
32.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 466757
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
56292
 
12.1%
e 41805
 
9.0%
o 33542
 
7.2%
a 33125
 
7.1%
r 31674
 
6.8%
s 31661
 
6.8%
t 25355
 
5.4%
n 24791
 
5.3%
i 21498
 
4.6%
l 17708
 
3.8%
Other values (72) 149306
32.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 466757
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
56292
 
12.1%
e 41805
 
9.0%
o 33542
 
7.2%
a 33125
 
7.1%
r 31674
 
6.8%
s 31661
 
6.8%
t 25355
 
5.4%
n 24791
 
5.3%
i 21498
 
4.6%
l 17708
 
3.8%
Other values (72) 149306
32.0%
Distinct6799
Distinct (%)1.2%
Missing2
Missing (%)< 0.1%
Memory size4.5 MiB
2025-03-26T16:27:55.793014image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length95
Median length75
Mean length36.76217067
Min length4

Characters and Unicode

Total characters21495025
Distinct characters74
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1458 ?
Unique (%)0.2%

Sample

1st rowNorth America, Costa Rica, Guanacaste
2nd rowNorth America, Jamaica
3rd rowAfrica, Zambia
4th rowNorth America, Panama, Cocle
5th rowAsia, China, Shanghai
ValueCountFrequency (%)
america 389978
 
13.6%
north 349209
 
12.1%
united 213210
 
7.4%
states 211533
 
7.4%
asia 94981
 
3.3%
south 88504
 
3.1%
africa 52986
 
1.8%
mexico 32547
 
1.1%
panama 31805
 
1.1%
colombia 28516
 
1.0%
Other values (4796) 1384154
48.1%
2025-03-26T16:27:55.995178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2292718
 
10.7%
a 2269312
 
10.6%
i 1576642
 
7.3%
e 1449846
 
6.7%
t 1415763
 
6.6%
r 1303234
 
6.1%
, 1293303
 
6.0%
o 1083368
 
5.0%
n 1034004
 
4.8%
s 709024
 
3.3%
Other values (64) 7067811
32.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21495025
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2292718
 
10.7%
a 2269312
 
10.6%
i 1576642
 
7.3%
e 1449846
 
6.7%
t 1415763
 
6.6%
r 1303234
 
6.1%
, 1293303
 
6.0%
o 1083368
 
5.0%
n 1034004
 
4.8%
s 709024
 
3.3%
Other values (64) 7067811
32.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21495025
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2292718
 
10.7%
a 2269312
 
10.6%
i 1576642
 
7.3%
e 1449846
 
6.7%
t 1415763
 
6.6%
r 1303234
 
6.1%
, 1293303
 
6.0%
o 1083368
 
5.0%
n 1034004
 
4.8%
s 709024
 
3.3%
Other values (64) 7067811
32.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21495025
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2292718
 
10.7%
a 2269312
 
10.6%
i 1576642
 
7.3%
e 1449846
 
6.7%
t 1415763
 
6.6%
r 1303234
 
6.1%
, 1293303
 
6.0%
o 1083368
 
5.0%
n 1034004
 
4.8%
s 709024
 
3.3%
Other values (64) 7067811
32.9%

continent
Text

Missing 

Distinct40
Distinct (%)< 0.1%
Missing12722
Missing (%)2.2%
Memory size4.5 MiB
2025-03-26T16:27:56.035437image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length35
Median length13
Mean length11.06585487
Min length4

Characters and Unicode

Total characters6329503
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowNorth America
2nd rowNorth America
3rd rowAfrica
4th rowNorth America
5th rowAsia
ValueCountFrequency (%)
america 389932
38.5%
north 338105
33.4%
asia 94981
 
9.4%
south 74555
 
7.4%
africa 47173
 
4.7%
ocean 25985
 
2.6%
pacific 19053
 
1.9%
europe 8238
 
0.8%
australia 6864
 
0.7%
atlantic 4033
 
0.4%
Other values (5) 4116
 
0.4%
2025-03-26T16:27:56.124943image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 791195
12.5%
a 598249
9.5%
i 584578
9.2%
A 543782
8.6%
c 506827
8.0%
441050
 
7.0%
t 429147
 
6.8%
e 424239
 
6.7%
o 420982
 
6.7%
h 412744
 
6.5%
Other values (17) 1176710
18.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6329503
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 791195
12.5%
a 598249
9.5%
i 584578
9.2%
A 543782
8.6%
c 506827
8.0%
441050
 
7.0%
t 429147
 
6.8%
e 424239
 
6.7%
o 420982
 
6.7%
h 412744
 
6.5%
Other values (17) 1176710
18.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6329503
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 791195
12.5%
a 598249
9.5%
i 584578
9.2%
A 543782
8.6%
c 506827
8.0%
441050
 
7.0%
t 429147
 
6.8%
e 424239
 
6.7%
o 420982
 
6.7%
h 412744
 
6.5%
Other values (17) 1176710
18.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6329503
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 791195
12.5%
a 598249
9.5%
i 584578
9.2%
A 543782
8.6%
c 506827
8.0%
441050
 
7.0%
t 429147
 
6.8%
e 424239
 
6.7%
o 420982
 
6.7%
h 412744
 
6.5%
Other values (17) 1176710
18.6%

waterBody
Text

Missing 

Distinct67
Distinct (%)0.3%
Missing558621
Missing (%)95.5%
Memory size4.5 MiB
2025-03-26T16:27:56.157243image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length55
Median length19
Mean length20.1426819
Min length8

Characters and Unicode

Total characters525442
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.1%

Sample

1st rowSouth Pacific Ocean
2nd rowPacific Ocean
3rd rowNorth Pacific Ocean
4th rowNorth Pacific Ocean
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 26064
32.3%
pacific 19053
23.6%
north 16053
19.9%
south 6723
 
8.3%
atlantic 4112
 
5.1%
indian 2690
 
3.3%
sea 2523
 
3.1%
mediterranean 1992
 
2.5%
weddell 131
 
0.2%
arctic 125
 
0.2%
Other values (57) 1126
 
1.4%
2025-03-26T16:27:56.249056image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 68678
13.1%
a 59300
11.3%
54506
10.4%
i 47461
9.0%
n 40107
 
7.6%
e 35331
 
6.7%
t 33369
 
6.4%
O 26090
 
5.0%
o 23138
 
4.4%
h 23032
 
4.4%
Other values (35) 114430
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 525442
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 68678
13.1%
a 59300
11.3%
54506
10.4%
i 47461
9.0%
n 40107
 
7.6%
e 35331
 
6.7%
t 33369
 
6.4%
O 26090
 
5.0%
o 23138
 
4.4%
h 23032
 
4.4%
Other values (35) 114430
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 525442
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 68678
13.1%
a 59300
11.3%
54506
10.4%
i 47461
9.0%
n 40107
 
7.6%
e 35331
 
6.7%
t 33369
 
6.4%
O 26090
 
5.0%
o 23138
 
4.4%
h 23032
 
4.4%
Other values (35) 114430
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 525442
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 68678
13.1%
a 59300
11.3%
54506
10.4%
i 47461
9.0%
n 40107
 
7.6%
e 35331
 
6.7%
t 33369
 
6.4%
O 26090
 
5.0%
o 23138
 
4.4%
h 23032
 
4.4%
Other values (35) 114430
21.8%
Distinct411
Distinct (%)0.1%
Missing5360
Missing (%)0.9%
Memory size4.5 MiB
2025-03-26T16:27:56.374937image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length33
Mean length10.04007098
Min length4

Characters and Unicode

Total characters5816685
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique54 ?
Unique (%)< 0.1%

Sample

1st rowCosta Rica
2nd rowJamaica
3rd rowZambia
4th rowPanama
5th rowChina
ValueCountFrequency (%)
united 213210
24.6%
states 211348
24.4%
colombia 28516
 
3.3%
mexico 28030
 
3.2%
panama 27140
 
3.1%
canada 17443
 
2.0%
thailand 17425
 
2.0%
philippines 16445
 
1.9%
china 14052
 
1.6%
islands 13825
 
1.6%
Other values (323) 278989
32.2%
2025-03-26T16:27:56.580190image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 731246
12.6%
t 721585
12.4%
e 577036
9.9%
i 510168
 
8.8%
n 497819
 
8.6%
s 311105
 
5.3%
d 305751
 
5.3%
287076
 
4.9%
U 228759
 
3.9%
S 225710
 
3.9%
Other values (51) 1420430
24.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5816685
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 731246
12.6%
t 721585
12.4%
e 577036
9.9%
i 510168
 
8.8%
n 497819
 
8.6%
s 311105
 
5.3%
d 305751
 
5.3%
287076
 
4.9%
U 228759
 
3.9%
S 225710
 
3.9%
Other values (51) 1420430
24.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5816685
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 731246
12.6%
t 721585
12.4%
e 577036
9.9%
i 510168
 
8.8%
n 497819
 
8.6%
s 311105
 
5.3%
d 305751
 
5.3%
287076
 
4.9%
U 228759
 
3.9%
S 225710
 
3.9%
Other values (51) 1420430
24.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5816685
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 731246
12.6%
t 721585
12.4%
e 577036
9.9%
i 510168
 
8.8%
n 497819
 
8.6%
s 311105
 
5.3%
d 305751
 
5.3%
287076
 
4.9%
U 228759
 
3.9%
S 225710
 
3.9%
Other values (51) 1420430
24.4%

stateProvince
Text

Missing 

Distinct2242
Distinct (%)0.5%
Missing93864
Missing (%)16.1%
Memory size4.5 MiB
2025-03-26T16:27:56.724073image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length71
Median length40
Mean length9.132447646
Min length3

Characters and Unicode

Total characters4482598
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)0.1%

Sample

1st rowGuanacaste
2nd rowCocle
3rd rowShanghai
4th rowChitinskaya Oblast'
5th rowJalisco
ValueCountFrequency (%)
california 23408
 
3.6%
new 20455
 
3.1%
alaska 19384
 
3.0%
virginia 14954
 
2.3%
arizona 13146
 
2.0%
maryland 10718
 
1.6%
florida 10644
 
1.6%
texas 9776
 
1.5%
columbia 9321
 
1.4%
island 9108
 
1.4%
Other values (2044) 512950
78.4%
2025-03-26T16:27:56.942838image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 688360
15.4%
i 363385
 
8.1%
n 330474
 
7.4%
o 310297
 
6.9%
r 284677
 
6.4%
e 240231
 
5.4%
l 198717
 
4.4%
s 197576
 
4.4%
163021
 
3.6%
t 158926
 
3.5%
Other values (57) 1546934
34.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4482598
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 688360
15.4%
i 363385
 
8.1%
n 330474
 
7.4%
o 310297
 
6.9%
r 284677
 
6.4%
e 240231
 
5.4%
l 198717
 
4.4%
s 197576
 
4.4%
163021
 
3.6%
t 158926
 
3.5%
Other values (57) 1546934
34.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4482598
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 688360
15.4%
i 363385
 
8.1%
n 330474
 
7.4%
o 310297
 
6.9%
r 284677
 
6.4%
e 240231
 
5.4%
l 198717
 
4.4%
s 197576
 
4.4%
163021
 
3.6%
t 158926
 
3.5%
Other values (57) 1546934
34.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4482598
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 688360
15.4%
i 363385
 
8.1%
n 330474
 
7.4%
o 310297
 
6.9%
r 284677
 
6.4%
e 240231
 
5.4%
l 198717
 
4.4%
s 197576
 
4.4%
163021
 
3.6%
t 158926
 
3.5%
Other values (57) 1546934
34.5%

county
Text

Missing 

Distinct3217
Distinct (%)1.4%
Missing353976
Missing (%)60.5%
Memory size4.5 MiB
2025-03-26T16:27:57.099669image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length39
Median length31
Mean length9.706957453
Min length1

Characters and Unicode

Total characters2239696
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique641 ?
Unique (%)0.3%

Sample

1st rowKrasnochikoiskiy Rayon
2nd rowRoosevelt
3rd rowHarrison
4th rowSouth Cotabato
5th rowLadysmith
ValueCountFrequency (%)
area 7116
 
2.1%
census 7108
 
2.1%
province 5993
 
1.8%
bergen 4929
 
1.5%
aleutians 4466
 
1.3%
county 4434
 
1.3%
west 4293
 
1.3%
borough 3776
 
1.1%
san 3629
 
1.1%
latah 3591
 
1.1%
Other values (2934) 288890
85.4%
2025-03-26T16:27:57.316123image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 243918
 
10.9%
e 199078
 
8.9%
n 164930
 
7.4%
o 159356
 
7.1%
r 146480
 
6.5%
i 116004
 
5.2%
107494
 
4.8%
t 103739
 
4.6%
s 98244
 
4.4%
l 97926
 
4.4%
Other values (59) 802527
35.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2239696
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 243918
 
10.9%
e 199078
 
8.9%
n 164930
 
7.4%
o 159356
 
7.1%
r 146480
 
6.5%
i 116004
 
5.2%
107494
 
4.8%
t 103739
 
4.6%
s 98244
 
4.4%
l 97926
 
4.4%
Other values (59) 802527
35.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2239696
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 243918
 
10.9%
e 199078
 
8.9%
n 164930
 
7.4%
o 159356
 
7.1%
r 146480
 
6.5%
i 116004
 
5.2%
107494
 
4.8%
t 103739
 
4.6%
s 98244
 
4.4%
l 97926
 
4.4%
Other values (59) 802527
35.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2239696
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 243918
 
10.9%
e 199078
 
8.9%
n 164930
 
7.4%
o 159356
 
7.1%
r 146480
 
6.5%
i 116004
 
5.2%
107494
 
4.8%
t 103739
 
4.6%
s 98244
 
4.4%
l 97926
 
4.4%
Other values (59) 802527
35.8%

locality
Text

Missing 

Distinct64312
Distinct (%)13.5%
Missing107553
Missing (%)18.4%
Memory size4.5 MiB
2025-03-26T16:27:57.466395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length929
Median length128
Mean length17.90106339
Min length1

Characters and Unicode

Total characters8541564
Distinct characters112
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33955 ?
Unique (%)7.1%

Sample

1st rowVolcan Rincon De La Vieja, S Slope, Hacienda Santa Maria
2nd rowLumsden, Near Claremont
3rd rowRio Guabal, Head, Tigre
4th rowShanghai
5th rowKrasnyi Chikoi, 98 km S, 97 km E, at upper Chikoi valley
ValueCountFrequency (%)
island 33525
 
2.4%
mi 31822
 
2.3%
of 23024
 
1.6%
river 22680
 
1.6%
rio 21871
 
1.6%
km 18527
 
1.3%
fort 14255
 
1.0%
san 13214
 
0.9%
near 13033
 
0.9%
lake 11919
 
0.8%
Other values (33477) 1203681
85.5%
2025-03-26T16:27:57.675122image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
930397
 
10.9%
a 914105
 
10.7%
e 542328
 
6.3%
o 540288
 
6.3%
n 525056
 
6.1%
i 502975
 
5.9%
r 415898
 
4.9%
l 354361
 
4.1%
t 336491
 
3.9%
s 280998
 
3.3%
Other values (102) 3198667
37.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8541564
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
930397
 
10.9%
a 914105
 
10.7%
e 542328
 
6.3%
o 540288
 
6.3%
n 525056
 
6.1%
i 502975
 
5.9%
r 415898
 
4.9%
l 354361
 
4.1%
t 336491
 
3.9%
s 280998
 
3.3%
Other values (102) 3198667
37.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8541564
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
930397
 
10.9%
a 914105
 
10.7%
e 542328
 
6.3%
o 540288
 
6.3%
n 525056
 
6.1%
i 502975
 
5.9%
r 415898
 
4.9%
l 354361
 
4.1%
t 336491
 
3.9%
s 280998
 
3.3%
Other values (102) 3198667
37.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8541564
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
930397
 
10.9%
a 914105
 
10.7%
e 542328
 
6.3%
o 540288
 
6.3%
n 525056
 
6.1%
i 502975
 
5.9%
r 415898
 
4.9%
l 354361
 
4.1%
t 336491
 
3.9%
s 280998
 
3.3%
Other values (102) 3198667
37.4%
Distinct1234
Distinct (%)1.4%
Missing498134
Missing (%)85.2%
Memory size4.5 MiB
2025-03-26T16:27:57.817402image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.434442609
Min length3

Characters and Unicode

Total characters470476
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique380 ?
Unique (%)0.4%

Sample

1st row475.0
2nd row1313.0
3rd row1006.0
4th row1524.0
5th row3353.0
ValueCountFrequency (%)
1829.0 2622
 
3.0%
914.0 2404
 
2.8%
1219.0 2324
 
2.7%
610.0 2187
 
2.5%
1524.0 2057
 
2.4%
1676.0 2012
 
2.3%
305.0 1843
 
2.1%
2134.0 1786
 
2.1%
1067.0 1656
 
1.9%
152.0 1483
 
1.7%
Other values (1223) 66199
76.5%
2025-03-26T16:27:58.031580image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 128139
27.2%
. 86573
18.4%
1 59890
12.7%
2 38753
 
8.2%
5 26494
 
5.6%
3 25785
 
5.5%
4 22372
 
4.8%
6 22227
 
4.7%
7 21408
 
4.6%
9 19562
 
4.2%
Other values (2) 19273
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 470476
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 128139
27.2%
. 86573
18.4%
1 59890
12.7%
2 38753
 
8.2%
5 26494
 
5.6%
3 25785
 
5.5%
4 22372
 
4.8%
6 22227
 
4.7%
7 21408
 
4.6%
9 19562
 
4.2%
Other values (2) 19273
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 470476
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 128139
27.2%
. 86573
18.4%
1 59890
12.7%
2 38753
 
8.2%
5 26494
 
5.6%
3 25785
 
5.5%
4 22372
 
4.8%
6 22227
 
4.7%
7 21408
 
4.6%
9 19562
 
4.2%
Other values (2) 19273
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 470476
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 128139
27.2%
. 86573
18.4%
1 59890
12.7%
2 38753
 
8.2%
5 26494
 
5.6%
3 25785
 
5.5%
4 22372
 
4.8%
6 22227
 
4.7%
7 21408
 
4.6%
9 19562
 
4.2%
Other values (2) 19273
 
4.1%
Distinct159
Distinct (%)1.6%
Missing574841
Missing (%)98.3%
Memory size4.5 MiB
2025-03-26T16:27:58.140406image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.591323738
Min length4

Characters and Unicode

Total characters55164
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st row671.0
2nd row2438.0
3rd row457.0
4th row1510.0
5th row305.0
ValueCountFrequency (%)
305.0 1116
 
11.3%
1219.0 787
 
8.0%
1524.0 446
 
4.5%
1981.0 429
 
4.3%
762.0 402
 
4.1%
2743.0 345
 
3.5%
1372.0 302
 
3.1%
1676.0 257
 
2.6%
610.0 250
 
2.5%
1829.0 195
 
2.0%
Other values (149) 5337
54.1%
2025-03-26T16:27:58.298837image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14093
25.5%
. 9866
17.9%
1 6345
11.5%
2 5370
 
9.7%
3 4072
 
7.4%
5 3319
 
6.0%
6 2684
 
4.9%
7 2580
 
4.7%
9 2427
 
4.4%
4 2353
 
4.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 55164
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 14093
25.5%
. 9866
17.9%
1 6345
11.5%
2 5370
 
9.7%
3 4072
 
7.4%
5 3319
 
6.0%
6 2684
 
4.9%
7 2580
 
4.7%
9 2427
 
4.4%
4 2353
 
4.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 55164
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 14093
25.5%
. 9866
17.9%
1 6345
11.5%
2 5370
 
9.7%
3 4072
 
7.4%
5 3319
 
6.0%
6 2684
 
4.9%
7 2580
 
4.7%
9 2427
 
4.4%
4 2353
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 55164
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 14093
25.5%
. 9866
17.9%
1 6345
11.5%
2 5370
 
9.7%
3 4072
 
7.4%
5 3319
 
6.0%
6 2684
 
4.9%
7 2580
 
4.7%
9 2427
 
4.4%
4 2353
 
4.3%

verbatimElevation
Text

Missing 

Distinct196
Distinct (%)15.4%
Missing583438
Missing (%)99.8%
Memory size4.5 MiB
2025-03-26T16:27:58.374097image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length84
Median length9
Mean length13.72813239
Min length3

Characters and Unicode

Total characters17421
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)8.5%

Sample

1st rowaltitude uncertain: front of label says 8300 ft, back of label says 10200-11000 ft
2nd rowca. 8800 ft
3rd rowsea level
4th rowsea level
5th rowsea level
ValueCountFrequency (%)
sea 769
20.9%
level 769
20.9%
ft 409
11.1%
ca 177
 
4.8%
m 115
 
3.1%
says 114
 
3.1%
label 100
 
2.7%
altitude 92
 
2.5%
uncertain 74
 
2.0%
of 67
 
1.8%
Other values (170) 986
26.9%
2025-03-26T16:27:58.513299image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17421
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17421
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17421
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 2820
16.2%
2403
13.8%
l 1955
11.2%
a 1546
8.9%
0 1357
 
7.8%
s 1076
 
6.2%
t 881
 
5.1%
v 812
 
4.7%
f 520
 
3.0%
n 353
 
2.0%
Other values (45) 3698
21.2%

decimalLatitude
Text

Missing 

Distinct3292
Distinct (%)11.8%
Missing556694
Missing (%)95.2%
Memory size4.5 MiB
2025-03-26T16:27:58.635621image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.238282226
Min length3

Characters and Unicode

Total characters146740
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1426 ?
Unique (%)5.1%

Sample

1st row49.644
2nd row1.73
3rd row6.45
4th row27.8273
5th row61.3053
ValueCountFrequency (%)
34.9606 991
 
3.5%
31.5011 663
 
2.4%
9.03 592
 
2.1%
8.25 507
 
1.8%
6.45 506
 
1.8%
29.3467 473
 
1.7%
3.65 448
 
1.6%
6.17 374
 
1.3%
12.63 310
 
1.1%
68.13 306
 
1.1%
Other values (3006) 22843
81.5%
2025-03-26T16:27:58.823042image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 28013
19.1%
3 14836
10.1%
1 14392
9.8%
5 12116
8.3%
6 11693
8.0%
8 11022
 
7.5%
4 10580
 
7.2%
7 10362
 
7.1%
2 9854
 
6.7%
0 9609
 
6.5%
Other values (2) 14263
9.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 146740
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 28013
19.1%
3 14836
10.1%
1 14392
9.8%
5 12116
8.3%
6 11693
8.0%
8 11022
 
7.5%
4 10580
 
7.2%
7 10362
 
7.1%
2 9854
 
6.7%
0 9609
 
6.5%
Other values (2) 14263
9.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 146740
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 28013
19.1%
3 14836
10.1%
1 14392
9.8%
5 12116
8.3%
6 11693
8.0%
8 11022
 
7.5%
4 10580
 
7.2%
7 10362
 
7.1%
2 9854
 
6.7%
0 9609
 
6.5%
Other values (2) 14263
9.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 146740
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 28013
19.1%
3 14836
10.1%
1 14392
9.8%
5 12116
8.3%
6 11693
8.0%
8 11022
 
7.5%
4 10580
 
7.2%
7 10362
 
7.1%
2 9854
 
6.7%
0 9609
 
6.5%
Other values (2) 14263
9.7%

decimalLongitude
Text

Missing 

Distinct3650
Distinct (%)13.0%
Missing556694
Missing (%)95.2%
Memory size4.5 MiB
2025-03-26T16:27:58.952440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length6.171099133
Min length3

Characters and Unicode

Total characters172871
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1665 ?
Unique (%)5.9%

Sample

1st row110.165
2nd row44.53
3rd row38.18
4th row-80.7089
5th row-149.812
ValueCountFrequency (%)
69.2778 991
 
3.5%
65.8453 663
 
2.4%
36.15 546
 
1.9%
38.18 502
 
1.8%
47.5206 473
 
1.7%
34.58 464
 
1.7%
52.37 452
 
1.6%
37.5 368
 
1.3%
165.95 306
 
1.1%
74.08 295
 
1.1%
Other values (3513) 22953
81.9%
2025-03-26T16:27:59.237596image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 28013
16.2%
7 19310
11.2%
1 16356
9.5%
- 15596
9.0%
3 14187
8.2%
5 13850
8.0%
2 12909
7.5%
6 12740
7.4%
8 12374
7.2%
9 10011
 
5.8%
Other values (2) 17525
10.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 172871
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 28013
16.2%
7 19310
11.2%
1 16356
9.5%
- 15596
9.0%
3 14187
8.2%
5 13850
8.0%
2 12909
7.5%
6 12740
7.4%
8 12374
7.2%
9 10011
 
5.8%
Other values (2) 17525
10.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 172871
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 28013
16.2%
7 19310
11.2%
1 16356
9.5%
- 15596
9.0%
3 14187
8.2%
5 13850
8.0%
2 12909
7.5%
6 12740
7.4%
8 12374
7.2%
9 10011
 
5.8%
Other values (2) 17525
10.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 172871
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 28013
16.2%
7 19310
11.2%
1 16356
9.5%
- 15596
9.0%
3 14187
8.2%
5 13850
8.0%
2 12909
7.5%
6 12740
7.4%
8 12374
7.2%
9 10011
 
5.8%
Other values (2) 17525
10.1%

geodeticDatum
Text

Missing 

Distinct2
Distinct (%)0.6%
Missing584348
Missing (%)99.9%
Memory size4.5 MiB
2025-03-26T16:27:59.282143image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.95821727
Min length17

Characters and Unicode

Total characters6447
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS 84 (EPSG:4326)
2nd rowWGS 84 (EPSG:4326)
3rd rowWGS 84 (EPSG:4326)
4th rowWGS 84 (EPSG:4326)
5th rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 344
32.4%
84 344
32.4%
epsg:4326 344
32.4%
nad83 15
 
1.4%
epsg:4269 15
 
1.4%
2025-03-26T16:27:59.367541image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 703
10.9%
703
10.9%
4 703
10.9%
G 703
10.9%
: 359
 
5.6%
) 359
 
5.6%
8 359
 
5.6%
( 359
 
5.6%
E 359
 
5.6%
P 359
 
5.6%
Other values (8) 1481
23.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6447
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 703
10.9%
703
10.9%
4 703
10.9%
G 703
10.9%
: 359
 
5.6%
) 359
 
5.6%
8 359
 
5.6%
( 359
 
5.6%
E 359
 
5.6%
P 359
 
5.6%
Other values (8) 1481
23.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6447
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 703
10.9%
703
10.9%
4 703
10.9%
G 703
10.9%
: 359
 
5.6%
) 359
 
5.6%
8 359
 
5.6%
( 359
 
5.6%
E 359
 
5.6%
P 359
 
5.6%
Other values (8) 1481
23.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6447
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 703
10.9%
703
10.9%
4 703
10.9%
G 703
10.9%
: 359
 
5.6%
) 359
 
5.6%
8 359
 
5.6%
( 359
 
5.6%
E 359
 
5.6%
P 359
 
5.6%
Other values (8) 1481
23.0%

verbatimLatitude
Text

Missing 

Distinct3459
Distinct (%)15.2%
Missing561920
Missing (%)96.1%
Memory size4.5 MiB
2025-03-26T16:27:59.490449image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length10
Mean length8.893491903
Min length2

Characters and Unicode

Total characters202656
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1703 ?
Unique (%)7.5%

Sample

1st row49 38.64 N
2nd row1 44 N
3rd row00 -- -- -
4th row06 27 -- N
5th row27.82728 N
ValueCountFrequency (%)
n 12411
 
18.1%
8370
 
12.2%
s 4463
 
6.5%
05 1518
 
2.2%
08 1303
 
1.9%
27 1303
 
1.9%
34 1214
 
1.8%
38 1144
 
1.7%
00 1076
 
1.6%
57 1070
 
1.6%
Other values (2075) 34716
50.6%
2025-03-26T16:27:59.677198image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
45801
22.6%
- 26954
13.3%
0 19701
9.7%
N 16646
 
8.2%
3 13125
 
6.5%
1 11462
 
5.7%
5 11193
 
5.5%
4 10614
 
5.2%
2 10536
 
5.2%
8 7706
 
3.8%
Other values (10) 28918
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 202656
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
45801
22.6%
- 26954
13.3%
0 19701
9.7%
N 16646
 
8.2%
3 13125
 
6.5%
1 11462
 
5.7%
5 11193
 
5.5%
4 10614
 
5.2%
2 10536
 
5.2%
8 7706
 
3.8%
Other values (10) 28918
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 202656
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
45801
22.6%
- 26954
13.3%
0 19701
9.7%
N 16646
 
8.2%
3 13125
 
6.5%
1 11462
 
5.7%
5 11193
 
5.5%
4 10614
 
5.2%
2 10536
 
5.2%
8 7706
 
3.8%
Other values (10) 28918
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 202656
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
45801
22.6%
- 26954
13.3%
0 19701
9.7%
N 16646
 
8.2%
3 13125
 
6.5%
1 11462
 
5.7%
5 11193
 
5.5%
4 10614
 
5.2%
2 10536
 
5.2%
8 7706
 
3.8%
Other values (10) 28918
14.3%

verbatimLongitude
Text

Missing 

Distinct3497
Distinct (%)16.1%
Missing563009
Missing (%)96.3%
Memory size4.5 MiB
2025-03-26T16:27:59.807084image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length13
Mean length9.71375242
Min length4

Characters and Unicode

Total characters210769
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1738 ?
Unique (%)8.0%

Sample

1st row110 09.91 E
2nd row44 32 E
3rd row140 -- -- W
4th row038 11 -- E
5th row-80.7089
ValueCountFrequency (%)
e 9828
 
14.8%
8666
 
13.1%
w 6456
 
9.7%
37 1471
 
2.2%
40 1114
 
1.7%
16 1052
 
1.6%
69 964
 
1.5%
00 934
 
1.4%
39 783
 
1.2%
30 738
 
1.1%
Other values (2292) 34297
51.7%
2025-03-26T16:27:59.991044image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44605
21.2%
- 26048
12.4%
0 21386
10.1%
1 17767
 
8.4%
3 13049
 
6.2%
E 10949
 
5.2%
2 10478
 
5.0%
4 10071
 
4.8%
W 10038
 
4.8%
6 9756
 
4.6%
Other values (10) 36622
17.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 210769
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
44605
21.2%
- 26048
12.4%
0 21386
10.1%
1 17767
 
8.4%
3 13049
 
6.2%
E 10949
 
5.2%
2 10478
 
5.0%
4 10071
 
4.8%
W 10038
 
4.8%
6 9756
 
4.6%
Other values (10) 36622
17.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 210769
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
44605
21.2%
- 26048
12.4%
0 21386
10.1%
1 17767
 
8.4%
3 13049
 
6.2%
E 10949
 
5.2%
2 10478
 
5.0%
4 10071
 
4.8%
W 10038
 
4.8%
6 9756
 
4.6%
Other values (10) 36622
17.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 210769
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
44605
21.2%
- 26048
12.4%
0 21386
10.1%
1 17767
 
8.4%
3 13049
 
6.2%
E 10949
 
5.2%
2 10478
 
5.0%
4 10071
 
4.8%
W 10038
 
4.8%
6 9756
 
4.6%
Other values (10) 36622
17.4%
Distinct4
Distinct (%)< 0.1%
Missing567398
Missing (%)97.0%
Memory size4.5 MiB
2025-03-26T16:28:00.028543image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.88075568
Min length3

Characters and Unicode

Total characters396043
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 17206
33.3%
minutes 17204
33.3%
seconds 17204
33.3%
utm 100
 
0.2%
unknown 3
 
< 0.1%
decimal 2
 
< 0.1%
2025-03-26T16:28:00.121409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 86028
21.7%
s 51614
13.0%
n 34417
 
8.7%
34410
 
8.7%
M 17304
 
4.4%
o 17207
 
4.3%
D 17206
 
4.3%
c 17206
 
4.3%
g 17206
 
4.3%
r 17206
 
4.3%
Other values (12) 86239
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 396043
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 86028
21.7%
s 51614
13.0%
n 34417
 
8.7%
34410
 
8.7%
M 17304
 
4.4%
o 17207
 
4.3%
D 17206
 
4.3%
c 17206
 
4.3%
g 17206
 
4.3%
r 17206
 
4.3%
Other values (12) 86239
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 396043
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 86028
21.7%
s 51614
13.0%
n 34417
 
8.7%
34410
 
8.7%
M 17304
 
4.4%
o 17207
 
4.3%
D 17206
 
4.3%
c 17206
 
4.3%
g 17206
 
4.3%
r 17206
 
4.3%
Other values (12) 86239
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 396043
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 86028
21.7%
s 51614
13.0%
n 34417
 
8.7%
34410
 
8.7%
M 17304
 
4.4%
o 17207
 
4.3%
D 17206
 
4.3%
c 17206
 
4.3%
g 17206
 
4.3%
r 17206
 
4.3%
Other values (12) 86239
21.8%

georeferenceProtocol
Text

Missing 

Distinct11
Distinct (%)0.9%
Missing583454
Missing (%)99.8%
Memory size4.5 MiB
2025-03-26T16:28:00.151224image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length3
Mean length7.130885874
Min length3

Characters and Unicode

Total characters8935
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st rowGoogle Earth maps
2nd rowGEOLocate tool
3rd rowGoogle Earth maps
4th rowGPS
5th rowMap
ValueCountFrequency (%)
gps 740
39.3%
earth 197
 
10.5%
maps 197
 
10.5%
google 197
 
10.5%
geolocate 179
 
9.5%
tool 179
 
9.5%
map 109
 
5.8%
online 18
 
1.0%
recorded 15
 
0.8%
not 15
 
0.8%
Other values (7) 35
 
1.9%
2025-03-26T16:28:00.239219image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 1117
12.5%
o 992
11.1%
P 740
 
8.3%
S 740
 
8.3%
a 704
 
7.9%
628
 
7.0%
t 584
 
6.5%
e 438
 
4.9%
l 415
 
4.6%
E 376
 
4.2%
Other values (23) 2201
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8935
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 1117
12.5%
o 992
11.1%
P 740
 
8.3%
S 740
 
8.3%
a 704
 
7.9%
628
 
7.0%
t 584
 
6.5%
e 438
 
4.9%
l 415
 
4.6%
E 376
 
4.2%
Other values (23) 2201
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8935
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 1117
12.5%
o 992
11.1%
P 740
 
8.3%
S 740
 
8.3%
a 704
 
7.9%
628
 
7.0%
t 584
 
6.5%
e 438
 
4.9%
l 415
 
4.6%
E 376
 
4.2%
Other values (23) 2201
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8935
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 1117
12.5%
o 992
11.1%
P 740
 
8.3%
S 740
 
8.3%
a 704
 
7.9%
628
 
7.0%
t 584
 
6.5%
e 438
 
4.9%
l 415
 
4.6%
E 376
 
4.2%
Other values (23) 2201
24.6%
Distinct5
Distinct (%)0.7%
Missing584013
Missing (%)99.9%
Memory size4.5 MiB
2025-03-26T16:28:00.267412image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length9
Mean length8.734870317
Min length3

Characters and Unicode

Total characters6062
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st rowuncertain
2nd rowuncertain
3rd rowuncertain
4th rowuncertain
5th rowuncertain
ValueCountFrequency (%)
uncertain 659
94.3%
cf 29
 
4.1%
sp 4
 
0.6%
aff 4
 
0.6%
near 2
 
0.3%
vel 1
 
0.1%
2025-03-26T16:28:00.349202image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1320
21.8%
c 688
11.3%
a 665
11.0%
e 662
10.9%
r 661
10.9%
u 659
10.9%
t 659
10.9%
i 659
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6062
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1320
21.8%
c 688
11.3%
a 665
11.0%
e 662
10.9%
r 661
10.9%
u 659
10.9%
t 659
10.9%
i 659
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6062
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1320
21.8%
c 688
11.3%
a 665
11.0%
e 662
10.9%
r 661
10.9%
u 659
10.9%
t 659
10.9%
i 659
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6062
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1320
21.8%
c 688
11.3%
a 665
11.0%
e 662
10.9%
r 661
10.9%
u 659
10.9%
t 659
10.9%
i 659
10.9%
f 37
 
0.6%
. 37
 
0.6%
Other values (5) 15
 
0.2%

typeStatus
Text

Missing 

Distinct8
Distinct (%)0.2%
Missing580729
Missing (%)99.3%
Memory size4.5 MiB
2025-03-26T16:28:00.382708image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length15
Median length4
Mean length4.654851684
Min length4

Characters and Unicode

Total characters18517
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rowCotype
2nd rowCotype
3rd rowCotype
4th rowCotype
5th rowCotype
ValueCountFrequency (%)
type 2764
69.1%
cotype 1217
30.4%
possible 12
 
0.3%
probable 5
 
0.1%
2025-03-26T16:28:00.470218image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3998
21.6%
y 3981
21.5%
p 3981
21.5%
T 2764
14.9%
o 1234
 
6.7%
C 1217
 
6.6%
t 1217
 
6.6%
s 24
 
0.1%
b 22
 
0.1%
20
 
0.1%
Other values (6) 59
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18517
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3998
21.6%
y 3981
21.5%
p 3981
21.5%
T 2764
14.9%
o 1234
 
6.7%
C 1217
 
6.6%
t 1217
 
6.6%
s 24
 
0.1%
b 22
 
0.1%
20
 
0.1%
Other values (6) 59
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18517
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3998
21.6%
y 3981
21.5%
p 3981
21.5%
T 2764
14.9%
o 1234
 
6.7%
C 1217
 
6.6%
t 1217
 
6.6%
s 24
 
0.1%
b 22
 
0.1%
20
 
0.1%
Other values (6) 59
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18517
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3998
21.6%
y 3981
21.5%
p 3981
21.5%
T 2764
14.9%
o 1234
 
6.7%
C 1217
 
6.6%
t 1217
 
6.6%
s 24
 
0.1%
b 22
 
0.1%
20
 
0.1%
Other values (6) 59
 
0.3%

identifiedBy
Text

Missing 

Distinct70
Distinct (%)2.1%
Missing581316
Missing (%)99.4%
Memory size4.5 MiB
2025-03-26T16:28:00.542795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length129
Median length18
Mean length24.98525509
Min length9

Characters and Unicode

Total characters84725
Distinct characters60
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)0.6%

Sample

1st rowWetmore, Alexander
2nd rowWetmore, Alexander
3rd rowWetmore, Alexander
4th rowWetmore, Alexander
5th rowHardy, John William
ValueCountFrequency (%)
wetmore 2393
21.8%
alexander 2382
21.7%
of 294
 
2.7%
united 271
 
2.5%
states 270
 
2.5%
268
 
2.4%
museum 246
 
2.2%
history 200
 
1.8%
natural 200
 
1.8%
birds 198
 
1.8%
Other values (179) 4234
38.6%
2025-03-26T16:28:00.681060image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 11587
13.7%
7565
 
8.9%
r 6604
 
7.8%
a 5108
 
6.0%
o 5033
 
5.9%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3972
 
4.7%
m 3199
 
3.8%
Other values (50) 28834
34.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 84725
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11587
13.7%
7565
 
8.9%
r 6604
 
7.8%
a 5108
 
6.0%
o 5033
 
5.9%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3972
 
4.7%
m 3199
 
3.8%
Other values (50) 28834
34.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 84725
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11587
13.7%
7565
 
8.9%
r 6604
 
7.8%
a 5108
 
6.0%
o 5033
 
5.9%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3972
 
4.7%
m 3199
 
3.8%
Other values (50) 28834
34.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 84725
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11587
13.7%
7565
 
8.9%
r 6604
 
7.8%
a 5108
 
6.0%
o 5033
 
5.9%
t 4517
 
5.3%
n 4224
 
5.0%
l 4082
 
4.8%
, 3972
 
4.7%
m 3199
 
3.8%
Other values (50) 28834
34.0%
Distinct22057
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:28:00.807624image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length65
Median length48
Mean length23.69780933
Min length7

Characters and Unicode

Total characters13856275
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3429 ?
Unique (%)0.6%

Sample

1st rowCatharus ustulatus swainsoni
2nd rowTrochilus polytmus polytmus
3rd rowButorides striatus
4th rowGlyphorynchus spirurus sublestus
5th rowPycnonotus sinensis sinensis
ValueCountFrequency (%)
dendroica 14825
 
1.0%
parus 7482
 
0.5%
melospiza 7108
 
0.5%
turdus 6811
 
0.5%
vireo 6405
 
0.4%
calidris 6376
 
0.4%
sterna 6183
 
0.4%
hyemalis 5963
 
0.4%
melodia 5930
 
0.4%
carduelis 5741
 
0.4%
Other values (10904) 1420078
95.1%
2025-03-26T16:28:01.018787image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1477761
 
10.7%
i 1303229
 
9.4%
s 1190459
 
8.6%
r 934227
 
6.7%
908195
 
6.6%
e 886026
 
6.4%
u 853988
 
6.2%
o 821499
 
5.9%
l 776614
 
5.6%
n 730695
 
5.3%
Other values (48) 3973582
28.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13856275
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1477761
 
10.7%
i 1303229
 
9.4%
s 1190459
 
8.6%
r 934227
 
6.7%
908195
 
6.6%
e 886026
 
6.4%
u 853988
 
6.2%
o 821499
 
5.9%
l 776614
 
5.6%
n 730695
 
5.3%
Other values (48) 3973582
28.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13856275
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1477761
 
10.7%
i 1303229
 
9.4%
s 1190459
 
8.6%
r 934227
 
6.7%
908195
 
6.6%
e 886026
 
6.4%
u 853988
 
6.2%
o 821499
 
5.9%
l 776614
 
5.6%
n 730695
 
5.3%
Other values (48) 3973582
28.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13856275
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1477761
 
10.7%
i 1303229
 
9.4%
s 1190459
 
8.6%
r 934227
 
6.7%
908195
 
6.6%
e 886026
 
6.4%
u 853988
 
6.2%
o 821499
 
5.9%
l 776614
 
5.6%
n 730695
 
5.3%
Other values (48) 3973582
28.7%
Distinct185
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:28:01.162321image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length89
Median length78
Mean length65.98136503
Min length45

Characters and Unicode

Total characters38579766
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowAnimalia, Chordata, Vertebrata, Aves, Passeriformes, Turdidae
2nd rowAnimalia, Chordata, Vertebrata, Aves, Apodiformes, Trochilidae
3rd rowAnimalia, Chordata, Vertebrata, Aves, Ciconiiformes, Ardeidae
4th rowAnimalia, Chordata, Vertebrata, Aves, Passeriformes, Dendrocolaptidae
5th rowAnimalia, Chordata, Vertebrata, Aves, Passeriformes, Pycnonotidae
ValueCountFrequency (%)
animalia 584707
16.0%
aves 584707
16.0%
chordata 584707
16.0%
vertebrata 584707
16.0%
passeriformes 372571
10.2%
emberizidae 72831
 
2.0%
emberizinae 50655
 
1.4%
charadriiformes 44075
 
1.2%
parulidae 36368
 
1.0%
tyrannidae 27492
 
0.8%
Other values (206) 702571
19.3%
2025-03-26T16:28:01.368637image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 5108777
13.2%
e 3705679
 
9.6%
r 3368309
 
8.7%
3060684
 
7.9%
, 3060683
 
7.9%
i 3036106
 
7.9%
s 1982452
 
5.1%
t 1944863
 
5.0%
o 1467591
 
3.8%
m 1357808
 
3.5%
Other values (37) 10486814
27.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38579766
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5108777
13.2%
e 3705679
 
9.6%
r 3368309
 
8.7%
3060684
 
7.9%
, 3060683
 
7.9%
i 3036106
 
7.9%
s 1982452
 
5.1%
t 1944863
 
5.0%
o 1467591
 
3.8%
m 1357808
 
3.5%
Other values (37) 10486814
27.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38579766
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5108777
13.2%
e 3705679
 
9.6%
r 3368309
 
8.7%
3060684
 
7.9%
, 3060683
 
7.9%
i 3036106
 
7.9%
s 1982452
 
5.1%
t 1944863
 
5.0%
o 1467591
 
3.8%
m 1357808
 
3.5%
Other values (37) 10486814
27.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38579766
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5108777
13.2%
e 3705679
 
9.6%
r 3368309
 
8.7%
3060684
 
7.9%
, 3060683
 
7.9%
i 3036106
 
7.9%
s 1982452
 
5.1%
t 1944863
 
5.0%
o 1467591
 
3.8%
m 1357808
 
3.5%
Other values (37) 10486814
27.2%

kingdom
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:28:01.408637image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4677656
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 584707
100.0%
2025-03-26T16:28:01.483931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1169414
25.0%
a 1169414
25.0%
A 584707
12.5%
n 584707
12.5%
m 584707
12.5%
l 584707
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4677656
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1169414
25.0%
a 1169414
25.0%
A 584707
12.5%
n 584707
12.5%
m 584707
12.5%
l 584707
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4677656
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1169414
25.0%
a 1169414
25.0%
A 584707
12.5%
n 584707
12.5%
m 584707
12.5%
l 584707
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4677656
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1169414
25.0%
a 1169414
25.0%
A 584707
12.5%
n 584707
12.5%
m 584707
12.5%
l 584707
12.5%

phylum
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:28:01.510933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4677656
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChordata
2nd rowChordata
3rd rowChordata
4th rowChordata
5th rowChordata
ValueCountFrequency (%)
chordata 584707
100.0%
2025-03-26T16:28:01.590611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1169414
25.0%
C 584707
12.5%
h 584707
12.5%
o 584707
12.5%
r 584707
12.5%
d 584707
12.5%
t 584707
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4677656
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1169414
25.0%
C 584707
12.5%
h 584707
12.5%
o 584707
12.5%
r 584707
12.5%
d 584707
12.5%
t 584707
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4677656
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1169414
25.0%
C 584707
12.5%
h 584707
12.5%
o 584707
12.5%
r 584707
12.5%
d 584707
12.5%
t 584707
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4677656
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1169414
25.0%
C 584707
12.5%
h 584707
12.5%
o 584707
12.5%
r 584707
12.5%
d 584707
12.5%
t 584707
12.5%

class
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:28:01.620611image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2338828
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAves
2nd rowAves
3rd rowAves
4th rowAves
5th rowAves
ValueCountFrequency (%)
aves 584707
100.0%
2025-03-26T16:28:01.703124image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 584707
25.0%
v 584707
25.0%
e 584707
25.0%
s 584707
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2338828
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 584707
25.0%
v 584707
25.0%
e 584707
25.0%
s 584707
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2338828
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 584707
25.0%
v 584707
25.0%
e 584707
25.0%
s 584707
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2338828
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 584707
25.0%
v 584707
25.0%
e 584707
25.0%
s 584707
25.0%

order
Text

Distinct23
Distinct (%)< 0.1%
Missing12
Missing (%)< 0.1%
Memory size4.5 MiB
2025-03-26T16:28:01.742451image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length13
Mean length12.92967616
Min length10

Characters and Unicode

Total characters7559917
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPasseriformes
2nd rowApodiformes
3rd rowCiconiiformes
4th rowPasseriformes
5th rowPasseriformes
ValueCountFrequency (%)
passeriformes 372571
63.7%
charadriiformes 44075
 
7.5%
piciformes 22596
 
3.9%
apodiformes 18145
 
3.1%
falconiformes 15872
 
2.7%
anseriformes 15673
 
2.7%
galliformes 14887
 
2.5%
columbiformes 13088
 
2.2%
coraciiformes 9455
 
1.6%
psittaciformes 7419
 
1.3%
Other values (13) 50914
 
8.7%
2025-03-26T16:28:01.840967image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 1352123
17.9%
r 1103620
14.6%
e 993641
13.1%
i 704862
9.3%
o 661554
8.8%
m 600360
7.9%
f 583289
7.7%
a 529330
 
7.0%
P 417773
 
5.5%
l 89985
 
1.2%
Other values (16) 523380
 
6.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7559917
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 1352123
17.9%
r 1103620
14.6%
e 993641
13.1%
i 704862
9.3%
o 661554
8.8%
m 600360
7.9%
f 583289
7.7%
a 529330
 
7.0%
P 417773
 
5.5%
l 89985
 
1.2%
Other values (16) 523380
 
6.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7559917
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 1352123
17.9%
r 1103620
14.6%
e 993641
13.1%
i 704862
9.3%
o 661554
8.8%
m 600360
7.9%
f 583289
7.7%
a 529330
 
7.0%
P 417773
 
5.5%
l 89985
 
1.2%
Other values (16) 523380
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7559917
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 1352123
17.9%
r 1103620
14.6%
e 993641
13.1%
i 704862
9.3%
o 661554
8.8%
m 600360
7.9%
f 583289
7.7%
a 529330
 
7.0%
P 417773
 
5.5%
l 89985
 
1.2%
Other values (16) 523380
 
6.9%

family
Text

Distinct170
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.5 MiB
2025-03-26T16:28:01.945220image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length15
Mean length10.09881872
Min length7

Characters and Unicode

Total characters5904850
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowTurdidae
2nd rowTrochilidae
3rd rowArdeidae
4th rowDendrocolaptidae
5th rowPycnonotidae
ValueCountFrequency (%)
emberizidae 72831
 
12.5%
parulidae 36368
 
6.2%
tyrannidae 27492
 
4.7%
turdidae 24864
 
4.3%
icteridae 19963
 
3.4%
picidae 17388
 
3.0%
scolopacidae 16645
 
2.8%
anatidae 15615
 
2.7%
fringillidae 15541
 
2.7%
sylviidae 15341
 
2.6%
Other values (160) 322660
55.2%
2025-03-26T16:28:02.120724image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 940750
15.9%
a 861009
14.6%
e 744386
12.6%
d 669537
11.3%
r 404321
 
6.8%
l 239353
 
4.1%
c 213303
 
3.6%
o 197992
 
3.4%
n 189958
 
3.2%
t 142864
 
2.4%
Other values (35) 1301377
22.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5904850
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 940750
15.9%
a 861009
14.6%
e 744386
12.6%
d 669537
11.3%
r 404321
 
6.8%
l 239353
 
4.1%
c 213303
 
3.6%
o 197992
 
3.4%
n 189958
 
3.2%
t 142864
 
2.4%
Other values (35) 1301377
22.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5904850
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 940750
15.9%
a 861009
14.6%
e 744386
12.6%
d 669537
11.3%
r 404321
 
6.8%
l 239353
 
4.1%
c 213303
 
3.6%
o 197992
 
3.4%
n 189958
 
3.2%
t 142864
 
2.4%
Other values (35) 1301377
22.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5904850
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 940750
15.9%
a 861009
14.6%
e 744386
12.6%
d 669537
11.3%
r 404321
 
6.8%
l 239353
 
4.1%
c 213303
 
3.6%
o 197992
 
3.4%
n 189958
 
3.2%
t 142864
 
2.4%
Other values (35) 1301377
22.0%

genus
Text

Distinct2021
Distinct (%)0.3%
Missing207
Missing (%)< 0.1%
Memory size4.5 MiB
2025-03-26T16:28:02.264001image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.461799829
Min length3

Characters and Unicode

Total characters4945922
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique79 ?
Unique (%)< 0.1%

Sample

1st rowCatharus
2nd rowTrochilus
3rd rowButorides
4th rowGlyphorynchus
5th rowPycnonotus
ValueCountFrequency (%)
dendroica 14824
 
2.5%
parus 7482
 
1.3%
melospiza 7108
 
1.2%
turdus 6811
 
1.2%
vireo 6404
 
1.1%
calidris 6372
 
1.1%
sterna 6183
 
1.1%
agelaius 5525
 
0.9%
carduelis 5506
 
0.9%
picoides 5085
 
0.9%
Other values (2011) 513200
87.8%
2025-03-26T16:28:02.544613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 519786
 
10.5%
i 398145
 
8.0%
o 387135
 
7.8%
s 383123
 
7.7%
r 365875
 
7.4%
u 308793
 
6.2%
e 307034
 
6.2%
l 267508
 
5.4%
n 224161
 
4.5%
c 212762
 
4.3%
Other values (42) 1571600
31.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4945922
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 519786
 
10.5%
i 398145
 
8.0%
o 387135
 
7.8%
s 383123
 
7.7%
r 365875
 
7.4%
u 308793
 
6.2%
e 307034
 
6.2%
l 267508
 
5.4%
n 224161
 
4.5%
c 212762
 
4.3%
Other values (42) 1571600
31.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4945922
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 519786
 
10.5%
i 398145
 
8.0%
o 387135
 
7.8%
s 383123
 
7.7%
r 365875
 
7.4%
u 308793
 
6.2%
e 307034
 
6.2%
l 267508
 
5.4%
n 224161
 
4.5%
c 212762
 
4.3%
Other values (42) 1571600
31.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4945922
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 519786
 
10.5%
i 398145
 
8.0%
o 387135
 
7.8%
s 383123
 
7.7%
r 365875
 
7.4%
u 308793
 
6.2%
e 307034
 
6.2%
l 267508
 
5.4%
n 224161
 
4.5%
c 212762
 
4.3%
Other values (42) 1571600
31.8%
Distinct4700
Distinct (%)0.8%
Missing979
Missing (%)0.2%
Memory size4.5 MiB
2025-03-26T16:28:02.677242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length17
Mean length8.777389469
Min length3

Characters and Unicode

Total characters5123608
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique320 ?
Unique (%)0.1%

Sample

1st rowustulatus
2nd rowpolytmus
3rd rowstriatus
4th rowspirurus
5th rowsinensis
ValueCountFrequency (%)
melodia 5114
 
0.9%
phoeniceus 4998
 
0.9%
hyemalis 4955
 
0.8%
americana 4689
 
0.8%
canadensis 3855
 
0.7%
sandwichensis 3773
 
0.6%
pusilla 3579
 
0.6%
alpestris 3382
 
0.6%
carolinensis 3308
 
0.6%
petechia 3061
 
0.5%
Other values (4690) 543014
93.0%
2025-03-26T16:28:02.877531image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 631455
12.3%
i 561610
11.0%
s 511812
10.0%
r 364770
 
7.1%
u 364636
 
7.1%
e 356797
 
7.0%
l 334859
 
6.5%
n 308177
 
6.0%
c 308095
 
6.0%
o 275440
 
5.4%
Other values (18) 1105957
21.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5123608
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 631455
12.3%
i 561610
11.0%
s 511812
10.0%
r 364770
 
7.1%
u 364636
 
7.1%
e 356797
 
7.0%
l 334859
 
6.5%
n 308177
 
6.0%
c 308095
 
6.0%
o 275440
 
5.4%
Other values (18) 1105957
21.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5123608
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 631455
12.3%
i 561610
11.0%
s 511812
10.0%
r 364770
 
7.1%
u 364636
 
7.1%
e 356797
 
7.0%
l 334859
 
6.5%
n 308177
 
6.0%
c 308095
 
6.0%
o 275440
 
5.4%
Other values (18) 1105957
21.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5123608
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 631455
12.3%
i 561610
11.0%
s 511812
10.0%
r 364770
 
7.1%
u 364636
 
7.1%
e 356797
 
7.0%
l 334859
 
6.5%
n 308177
 
6.0%
c 308095
 
6.0%
o 275440
 
5.4%
Other values (18) 1105957
21.6%

infraspecificEpithet
Text

Missing 

Distinct7411
Distinct (%)2.3%
Missing268452
Missing (%)45.9%
Memory size4.5 MiB
2025-03-26T16:28:03.011689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.928001138
Min length2

Characters and Unicode

Total characters2823525
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique869 ?
Unique (%)0.3%

Sample

1st rowswainsoni
2nd rowpolytmus
3rd rowsublestus
4th rowsinensis
5th rowleucocephala
ValueCountFrequency (%)
carolinensis 1803
 
0.6%
pusilla 1304
 
0.4%
pinus 1235
 
0.4%
frontalis 1216
 
0.4%
coronata 1201
 
0.4%
occidentalis 1189
 
0.4%
arizonae 1067
 
0.3%
olivaceus 1061
 
0.3%
flammea 1046
 
0.3%
hyemalis 1005
 
0.3%
Other values (7396) 304157
96.2%
2025-03-26T16:28:03.208015image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 337766
12.0%
a 320912
11.4%
s 290534
10.3%
e 217876
 
7.7%
r 199495
 
7.1%
n 194556
 
6.9%
u 177627
 
6.3%
l 170758
 
6.0%
o 156038
 
5.5%
c 147679
 
5.2%
Other values (21) 610284
21.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2823525
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 337766
12.0%
a 320912
11.4%
s 290534
10.3%
e 217876
 
7.7%
r 199495
 
7.1%
n 194556
 
6.9%
u 177627
 
6.3%
l 170758
 
6.0%
o 156038
 
5.5%
c 147679
 
5.2%
Other values (21) 610284
21.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2823525
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 337766
12.0%
a 320912
11.4%
s 290534
10.3%
e 217876
 
7.7%
r 199495
 
7.1%
n 194556
 
6.9%
u 177627
 
6.3%
l 170758
 
6.0%
o 156038
 
5.5%
c 147679
 
5.2%
Other values (21) 610284
21.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2823525
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 337766
12.0%
a 320912
11.4%
s 290534
10.3%
e 217876
 
7.7%
r 199495
 
7.1%
n 194556
 
6.9%
u 177627
 
6.3%
l 170758
 
6.0%
o 156038
 
5.5%
c 147679
 
5.2%
Other values (21) 610284
21.6%

taxonRank
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing268452
Missing (%)45.9%
Memory size4.5 MiB
2025-03-26T16:28:03.252472image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters3162550
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsubspecies
2nd rowsubspecies
3rd rowsubspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 316255
100.0%
2025-03-26T16:28:03.331402image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 948765
30.0%
e 632510
20.0%
u 316255
 
10.0%
b 316255
 
10.0%
p 316255
 
10.0%
c 316255
 
10.0%
i 316255
 
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3162550
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 948765
30.0%
e 632510
20.0%
u 316255
 
10.0%
b 316255
 
10.0%
p 316255
 
10.0%
c 316255
 
10.0%
i 316255
 
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3162550
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 948765
30.0%
e 632510
20.0%
u 316255
 
10.0%
b 316255
 
10.0%
p 316255
 
10.0%
c 316255
 
10.0%
i 316255
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3162550
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 948765
30.0%
e 632510
20.0%
u 316255
 
10.0%
b 316255
 
10.0%
p 316255
 
10.0%
c 316255
 
10.0%
i 316255
 
10.0%
Distinct148
Distinct (%)13.0%
Missing583567
Missing (%)99.8%
Memory size4.5 MiB
2025-03-26T16:28:03.386909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length42
Median length31
Mean length8.010526316
Min length3

Characters and Unicode

Total characters9132
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)7.2%

Sample

1st rowRidgway
2nd rowOberholser
3rd rowTownsend
4th rowWetmore
5th rowRidgway
ValueCountFrequency (%)
ridgway 309
22.4%
wetmore 118
 
8.6%
nelson 113
 
8.2%
deignan 85
 
6.2%
oberholser 79
 
5.7%
47
 
3.4%
phillips 42
 
3.0%
baird 40
 
2.9%
ripley 30
 
2.2%
riley 27
 
2.0%
Other values (134) 489
35.5%
2025-03-26T16:28:03.512233image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 969
 
10.6%
i 699
 
7.7%
a 650
 
7.1%
r 569
 
6.2%
n 568
 
6.2%
o 526
 
5.8%
l 495
 
5.4%
d 447
 
4.9%
g 424
 
4.6%
s 415
 
4.5%
Other values (40) 3370
36.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9132
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 969
 
10.6%
i 699
 
7.7%
a 650
 
7.1%
r 569
 
6.2%
n 568
 
6.2%
o 526
 
5.8%
l 495
 
5.4%
d 447
 
4.9%
g 424
 
4.6%
s 415
 
4.5%
Other values (40) 3370
36.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9132
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 969
 
10.6%
i 699
 
7.7%
a 650
 
7.1%
r 569
 
6.2%
n 568
 
6.2%
o 526
 
5.8%
l 495
 
5.4%
d 447
 
4.9%
g 424
 
4.6%
s 415
 
4.5%
Other values (40) 3370
36.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9132
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 969
 
10.6%
i 699
 
7.7%
a 650
 
7.1%
r 569
 
6.2%
n 568
 
6.2%
o 526
 
5.8%
l 495
 
5.4%
d 447
 
4.9%
g 424
 
4.6%
s 415
 
4.5%
Other values (40) 3370
36.9%